调试

App.vue

@@ -4,19 +4,22 @@
 		getToken
 	} from '@/common/auth.js'
 	export default {
+		onLoad(e) {
+			console.log("wwwww",e);
+		},
 		onLaunch: function() {
-			// if (getToken()) {
-			// 	console.log('存在');
-			// 	uni.reLaunch({
-			// 		url: '/pages/index/index'
-			// 	})
+			if (getToken()) {
+				console.log('存在');
+				// uni.reLaunch({
+				// 	url: '/pages/index/index'
+				// })
 
-			// } else {
-			// 	console.log('不存在');
-			// 	uni.reLaunch({
-			// 		url: '/pages/login/index'
-			// 	})
-			// }
+			} else {
+				console.log('不存在');
+				uni.reLaunch({
+					url: '/pages/login/index'
+				})
+			}
 			// routingIntercept()
 			console.log('App Launch')
 		},

common/tracking.js/.bowerrc

@@ -1,3 +0,0 @@
-{
-  "directory": "../"
-}

common/tracking.js/.editorconfig

@@ -1,14 +0,0 @@
-# editorconfig.org
-root = true
-
-[*]
-indent_style = tab
-end_of_line = lf
-charset = utf-8
-trim_trailing_whitespace = true
-insert_final_newline = true
-indent_style = space
-indent_size = 2
-
-[*.md]
-trim_trailing_whitespace = false

common/tracking.js/.gitignore

@@ -1,3 +0,0 @@
-.DS_Store
-node_modules
-test/assets/benchmark.json

common/tracking.js/.jshintrc

@@ -1,30 +0,0 @@
-{
-  "asi": false,
-  "bitwise": false,
-  "curly": true,
-  "eqeqeq": true,
-  "esnext": true,
-  "evil": false,
-  "forin": false,
-  "globals": {
-    "document": true,
-    "navigator": true,
-    "tracking": true,
-    "window": true
-  },
-  "immed": true,
-  "indent": 2,
-  "lastsemic": false,
-  "maxdepth": false,
-  "multistr": false,
-  "newcap": true,
-  "noarg": true,
-  "node": true,
-  "onevar": false,
-  "quotmark": "single",
-  "regexp": true,
-  "smarttabs": true,
-  "trailing": true,
-  "undef": true,
-  "unused": true
-}

common/tracking.js/.travis.yml

@@ -1,4 +0,0 @@
-language: node_js
-node_js:
-  - "0.11"
-  - "0.10"

common/tracking.js/LICENSE.md

@@ -1,30 +0,0 @@
-Software License Agreement (BSD License)
-
-Copyright (c) 2014, Eduardo A. Lundgren Melo.
-All rights reserved.
-
-Redistribution and use of this software in source and binary forms, with or without modification, are
-permitted provided that the following conditions are met:
-
-* Redistributions of source code must retain the above
-  copyright notice, this list of conditions and the
-  following disclaimer.
-
-* Redistributions in binary form must reproduce the above
-  copyright notice, this list of conditions and the
-  following disclaimer in the documentation and/or other
-  materials provided with the distribution.
-
-* The name of Eduardo A. Lundgren Melo may not be used to endorse or promote products
-  derived from this software without specific prior
-  written permission of Eduardo A. Lundgren Melo.
-
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED
-WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
-PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
-ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
-LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
-INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR
-TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-

common/tracking.js/TODO.md

@@ -1,37 +0,0 @@
-### Face tracking
-- DONE display line with the face
-- impressive speed and accuracy from @clmtrackr - https://github.com/auduno/clmtrackr
-- http://blog.dlib.net/2014/08/real-time-face-pose-estimation.html
-  - dlib implementation
-- PerspectiveCamera.setViewOffset - todo the https://www.youtube.com/watch?v=LEPvUfC7wh8
-- support for webworker ?
-  - it consume a lot of cpu
-- try blur in source image
-- get a video on the internet to use as example
-- DONE do lerp on output 
-
----
-
-### Misc
-- fix image source
-- handle a proper versioning
-  - master is last stable
-  - stable is tagged in github repo
-  - dev is 'next-stable'
-
-- Tracking.Image without destination buffer - force reallocation
-  - allow to provide destination, if not present, 
-- three.js is r67 in the examples - current three.js is r86
-  - TODO port on current three.js
-- some examples are not running well - list which one
-  - webcam one ?
-- some examples are unclear - no instructions 
-  - provide info in color tracking on how to run it
-  - TODO list which one
-- add more interactive examples - stuff i can try with a webcam
-- merge lots of good PR
-  - https://github.com/eduardolundgren/tracking.js/pull/229 - Add support for Safari 11
-  - https://github.com/eduardolundgren/tracking.js/pull/144 Regressing Local Binary Features more details on face detection
-  - https://github.com/eduardolundgren/tracking.js/pull/164 - Creating conversor from haarcascade to tracking.js array
-  - https://github.com/eduardolundgren/tracking.js/pull/131 <- merge or close
-- ```gulp test``` fails in the benchmarks

common/tracking.js/assets/opencv_haarcascade_converter.html

@@ -1,101 +0,0 @@
-<!DOCTYPE HTML>
-<html lang="en-US">
-<head>
-	<meta charset="UTF-8">
-	<title></title>
-
-	<script type="text/javascript" src="opencv_haarcascade_frontalface_alt.js"></script>
-	<script type="text/javascript" src="opencv_haarcascade_eye.js"></script>
-	<script type="text/javascript" src="opencv_haarcascade_upper_body.js"></script>
-	<script type="text/javascript" src="opencv_haarcascade_mouth.js"></script>
-</head>
-<body>
-	<script>
-		// [
-		// 	[
-		// 		-1, // index
-		// 		0.8226894140243530, // stage threshold
-		//		// tree
-		// 		[
-		//			// node 1
-		// 			[
-		// 				3, 7, 14, 4, -1, // rect1
-		// 				3, 9, 14, 2, 2, // rect 2
-		// 				4.0141958743333817e-003, // node threshold
-		// 				0.0337941907346249, // left
-		// 				0.8378106951713562 // right
-		// 			],
-		//			// node 2
-		// 			[
-		// 				3, 7, 14, 4, -1,
-		// 				3, 9, 14, 2, 2,
-		// 				4.0141958743333817e-003,
-		// 				0.0337941907346249,
-		// 				0.8378106951713562
-		// 			]
-		// 		]
-		// 	]
-		// ];
-
-		var toFloat = function(v) {
-			// return parseFloat(parseFloat(v).toFixed(1));
-			return parseFloat(v);
-		},
-
-		toInt = function(v) {
-			return parseInt(v, 10);
-		},
-
-		convert = function(haarcascade) {
-			var stages = [],
-				hstages = haarcascade.stages,
-				i,
-				j;
-
-			for (i = 0; i < hstages.length; i++) {
-				var stage = [],
-					trees = [],
-					hstage = hstages[i],
-					htrees = hstage.trees,
-					parent = toInt(hstage.parent),
-					stageThreshold = toFloat(hstage.stage_threshold);
-
-				for (j = 0; j < htrees.length; j++) {
-					var node = [],
-						hnode = htrees[j][0],
-						hnodeThreshold = toFloat(hnode.threshold),
-						hnodeLeft = toFloat(hnode.left_val),
-						hnodeRight = toFloat(hnode.right_val),
-						hnodeRects = hnode.feature.rects,
-						hr,
-						r;
-
-						for (r = 0; r < hnodeRects.length; r++) {
-							hr = hnodeRects[r].split(" ").map(toFloat),
-							node = node.concat(hr);
-						}
-
-						node.push(hnodeThreshold, hnodeLeft, hnodeRight);
-						trees.push(node);
-				}
-
-				stage.push(parent, stageThreshold, trees);
-				stages.push(stage);
-			}
-
-			console.log(stages);
-
-			return JSON.stringify(stages);
-		};
-
-		// output
-
-		// var json = convert(opencv_haarcascade_frontalface_alt);
-		// var json = convert(opencv_haarcascade_eye);
-		// var json = convert(opencv_haarcascade_upper_body);
-		var json = convert(opencv_haarcascade_mouth);
-
-		console.log(json);
-	</script>
-</body>
-</html>

common/tracking.js/bower.json

@@ -1,22 +0,0 @@
-{
-  "name": "tracking",
-  "homepage": "http://trackingjs.com",
-  "authors": [
-    "Eduardo Lundgren <edu@rdo.io>"
-  ],
-  "description": "Augmented Reality JavaScript Framework.",
-  "main": "build/tracking.js",
-  "keywords": [
-    "tracking",
-    "webrtc"
-  ],
-  "license": "BSD",
-  "ignore": [
-    "**/.*",
-    "node_modules"
-  ],
-  "dependencies": {
-    "dat-gui": "0.5.0",
-    "threejs": "r67"
-  }
-}

common/tracking.js/examples/assets/color_camera_gui.js

@@ -1,94 +0,0 @@
-function initGUIControllers(tracker) {
-  // GUI Controllers
-
-  var gui = new dat.GUI();
-
-  var trackedColors = {
-    custom: false
-  };
-
-  Object.keys(tracking.ColorTracker.knownColors_).forEach(function(color) {
-    trackedColors[color] = true;
-  });
-
-  tracker.customColor = '#000000';
-
-  function createCustomColor(value) {
-    var components = /^#?([a-f\d]{2})([a-f\d]{2})([a-f\d]{2})$/i.exec(value);
-    var customColorR = parseInt(components[1], 16);
-    var customColorG = parseInt(components[2], 16);
-    var customColorB = parseInt(components[3], 16);
-
-    var colorTotal = customColorR + customColorG + customColorB;
-
-    if (colorTotal === 0) {
-      tracking.ColorTracker.registerColor('custom', function(r, g, b) {
-        return r + g + b < 10;
-      });
-    } else {
-      var rRatio = customColorR / colorTotal;
-      var gRatio = customColorG / colorTotal;
-
-      tracking.ColorTracker.registerColor('custom', function(r, g, b) {
-        var colorTotal2 = r + g + b;
-
-        if (colorTotal2 === 0) {
-          if (colorTotal < 10) {
-            return true;
-          }
-          return false;
-        }
-
-        var rRatio2 = r / colorTotal2,
-          gRatio2 = g / colorTotal2,
-          deltaColorTotal = colorTotal / colorTotal2,
-          deltaR = rRatio / rRatio2,
-          deltaG = gRatio / gRatio2;
-
-        return deltaColorTotal > 0.9 && deltaColorTotal < 1.1 &&
-          deltaR > 0.9 && deltaR < 1.1 &&
-          deltaG > 0.9 && deltaG < 1.1;
-      });
-    }
-
-    updateColors();
-  }
-
-  function updateColors() {
-    var colors = [];
-
-    for (var color in trackedColors) {
-      if (trackedColors[color]) {
-        colors.push(color);
-      }
-    }
-
-    tracker.setColors(colors);
-  }
-
-  var colorsFolder = gui.addFolder('Colors');
-
-  Object.keys(trackedColors).forEach(function(color) {
-    if (color !== 'custom') {
-      colorsFolder.add(trackedColors, color).onFinishChange(updateColors);
-    }
-  });
-
-  colorsFolder.add(trackedColors, 'custom').onFinishChange(function(value) {
-    if (value) {
-      this.customColorElement = colorsFolder.addColor(tracker, 'customColor').onChange(createCustomColor);
-    } else {
-      colorsFolder.remove(this.customColorElement);
-    }
-  });
-
-  var parametersFolder = gui.addFolder('Parameters');
-
-  parametersFolder.add(tracker, 'minDimension', 1, 100);
-  parametersFolder.add(tracker, 'minGroupSize', 1, 100);
-
-  colorsFolder.open();
-  parametersFolder.open();
-
-  updateColors();
-}

common/tracking.js/examples/assets/demo.css

@@ -1,57 +0,0 @@
-* {
-  margin: 0;
-  padding: 0;
-  font-family: Helvetica, Arial, sans-serif;
-}
-
-.demo-title {
-  position: absolute;
-  width: 100%;
-  background: #2e2f33;
-  z-index: 2;
-  padding: .7em 0;
-}
-
-.demo-title a {
-  color: #fff;
-  border-bottom: 1px dotted #a64ceb;
-  text-decoration: none;
-}
-
-.demo-title p {
-  color: #fff;
-  text-align: center;
-  text-transform: lowercase;
-  font-size: 15px;
-}
-
-.demo-frame {
-  background: url(frame.png) no-repeat;
-  width: 854px;
-  height: 658px;
-  position: fixed;
-  top: 50%;
-  left: 50%;
-  margin: -329px 0 0 -429px;
-  padding: 95px 20px 45px 34px;
-  overflow: hidden;
-  -webkit-box-sizing: border-box;
-  -moz-box-sizing: border-box;
-  -ms-box-sizing: border-box;
-  box-sizing: border-box;
-}
-
-.demo-container {
-  width: 100%;
-  height: 530px;
-  position: relative;
-  background: #eee;
-  overflow: hidden;
-  border-bottom-right-radius: 10px;
-  border-bottom-left-radius: 10px;
-}
-
-.dg.ac {
-  z-index: 100 !important;
-  top: 50px !important;
-}

common/tracking.js/examples/assets/fish_tank/FishTankRenderer.js

@@ -1,111 +0,0 @@
-(function() {
-
-  var FishTankRenderer = function() {};
-
-  FishTankRenderer.prototype.init = function(container) {
-    if (!FishTankRenderer.isWebGLEnabled()) {
-      throw new Error('WebGL is not enabled in your browser.');
-    }
-
-    var mesh, geometry;
-
-    this.spheres = [];
-
-    this.camera = new THREE.PerspectiveCamera(60, window.innerWidth / window.innerHeight, 1, 100000);
-    this.camera.position.z = 3200;
-
-    this.scene = new THREE.Scene();
-
-    var geometry = new THREE.SphereGeometry(100, 32, 16);
-
-    var path = 'assets/fish_tank/';
-    var format = '.png';
-    var urls = [
-      path + 'px' + format, path + 'nx' + format,
-      path + 'py' + format, path + 'ny' + format,
-      path + 'pz' + format, path + 'nz' + format
-    ];
-
-    var textureCube = THREE.ImageUtils.loadTextureCube(urls);
-    var material = new THREE.MeshBasicMaterial({
-      color: 0xffffff,
-      envMap: textureCube
-    });
-
-    for (var i = 0; i < 500; i++) {
-
-      var mesh = new THREE.Mesh(geometry, material);
-
-      mesh.position.x = Math.random() * 100000 - 50000;
-      mesh.position.y = Math.random() * 100000 - 50000;
-      mesh.position.z = Math.random() * 100000 - 50000;
-
-      mesh.scale.x = mesh.scale.y = mesh.scale.z = Math.random() * 3 + 1;
-
-      this.scene.add(mesh);
-
-      this.spheres.push(mesh);
-
-    }
-
-    // Skybox
-
-    var shader = THREE.ShaderLib["cube"];
-    shader.uniforms["tCube"].value = textureCube;
-
-    var material = new THREE.ShaderMaterial({
-
-        fragmentShader: shader.fragmentShader,
-        vertexShader: shader.vertexShader,
-        uniforms: shader.uniforms,
-        side: THREE.BackSide
-
-      }),
-
-      mesh = new THREE.Mesh(new THREE.BoxGeometry(100000, 100000, 100000), material);
-    this.scene.add(mesh);
-
-    var _params = {
-      minFilter: THREE.LinearFilter,
-      magFilter: THREE.NearestFilter,
-      format: THREE.RGBAFormat
-    };
-
-    var width = window.innerWidth || 2;
-    var height = window.innerHeight || 2;
-
-    this.renderer = new THREE.WebGLRenderer(width, height, _params);
-    container.appendChild(this.renderer.domElement);
-    this.renderer.setSize(width, height);
-  };
-
-  FishTankRenderer.prototype.render = function(controlX, controlY) {
-    var timer = 0.0001 * Date.now();
-
-    this.camera.position.x += (-controlX - this.camera.position.x) * 0.05;
-    this.camera.position.y += (-controlY - this.camera.position.y) * 0.05;
-
-    this.camera.lookAt(this.scene.position);
-
-    for (var i = 0, il = this.spheres.length; i < il; i++) {
-      var sphere = this.spheres[i];
-      sphere.position.x += 50 * Math.cos(timer + i);
-      sphere.position.y += 50 * Math.sin(timer + i * 1.1);
-    }
-
-    this.renderer.render(this.scene, this.camera);
-  };
-
-  FishTankRenderer.isWebGLEnabled = function() {
-    try {
-      var canvas = document.createElement('canvas');
-      return !!window.WebGLRenderingContext &&
-        (canvas.getContext('webgl') || canvas.getContext('experimental-webgl'));
-    } catch (e) {
-      return false;
-    }
-  };
-
-  window.FishTankRenderer = FishTankRenderer;
-
-})();

common/tracking.js/examples/brief.html

@@ -1,105 +0,0 @@
-<!doctype html>
-
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - feature matching</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-  <script src="../node_modules/dat.gui/build/dat.gui.min.js"></script>
-
-  <style>
-  .demo-container {
-    background-color: black;
-  }
-  #image1, #image2 {
-    position: absolute;
-    left: -1000px;
-    top: -1000px;
-  }
-  #canvas {
-    position: absolute;
-    left: 50%;
-    top: 50%;
-    margin-left: -393px;
-    margin-top: -147px;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － match similar feature points in two images</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <img id="image1" src="assets/brief1.png" />
-      <img id="image2" src="assets/brief2.png" />
-      <canvas id="canvas" width="786" height="295"></canvas>
-    </div>
-  </div>
-
-  <script>
-  window.onload = function() {
-    var width = 393;
-    var height = 295;
-    var canvas = document.getElementById('canvas');
-    var context = canvas.getContext('2d');
-
-    var image1 = document.getElementById('image1');
-    var image2 = document.getElementById('image2');
-
-    window.descriptorLength = 256;
-    window.matchesShown = 30;
-    window.blurRadius = 3;
-
-    var doMatch = function() {
-      tracking.Brief.N = window.descriptorLength;
-
-      context.drawImage(image1, 0, 0, width, height);
-      context.drawImage(image2, width, 0, width, height);
-  
-      var imageData1 = context.getImageData(0, 0, width, height);
-      var imageData2 = context.getImageData(width, 0, width, height);
-  
-      var gray1 = tracking.Image.grayscale(tracking.Image.blur(imageData1.data, width, height, blurRadius), width, height);
-      var gray2 = tracking.Image.grayscale(tracking.Image.blur(imageData2.data, width, height, blurRadius), width, height);
-  
-      var corners1 = tracking.Fast.findCorners(gray1, width, height);
-      var corners2 = tracking.Fast.findCorners(gray2, width, height);
-  
-      var descriptors1 = tracking.Brief.getDescriptors(gray1, width, corners1);
-      var descriptors2 = tracking.Brief.getDescriptors(gray2, width, corners2);
-  
-      var matches = tracking.Brief.reciprocalMatch(corners1, descriptors1, corners2, descriptors2);
-
-      matches.sort(function(a, b) {
-        return b.confidence - a.confidence;
-      });
-  
-      for (var i = 0; i < Math.min(window.matchesShown, matches.length); i++) {
-        var color = '#' + Math.floor(Math.random()*16777215).toString(16);
-        context.fillStyle = color;
-        context.strokeStyle = color;
-        context.fillRect(matches[i].keypoint1[0], matches[i].keypoint1[1], 4, 4);
-        context.fillRect(matches[i].keypoint2[0] + width, matches[i].keypoint2[1], 4, 4);
-
-        context.beginPath();
-        context.moveTo(matches[i].keypoint1[0], matches[i].keypoint1[1]);
-        context.lineTo(matches[i].keypoint2[0] + width, matches[i].keypoint2[1]);
-        context.stroke();
-
-      }
-    };
-
-    doMatch();
-
-    var gui = new dat.GUI();
-    gui.add(window, 'descriptorLength', 128, 512).step(32).onChange(doMatch);
-    gui.add(window, 'matchesShown', 1, 100).onChange(doMatch);
-    gui.add(window, 'blurRadius', 1.1, 5).onChange(doMatch);
-  }
-  </script>
-</body>
-</html>

common/tracking.js/examples/brief_camera.html

@@ -1,185 +0,0 @@
-<!doctype html>
-<html>
-<head>
-
-  <title>tracking.js - bounding box with camera</title>
-
-  <meta charset="utf-8">
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-   <script src="../node_modules/dat.gui/build/dat.gui.min.js"></script>
-  <script src="assets/stats.min.js"></script>
-
-  <style>
-  #boundingBox {
-    display: none;
-    position: absolute;
-    background: white;
-    border: 1px dashed;
-    opacity: .5;
-    z-index: 1;
-  }
-  #video {
-    position: absolute;
-    top: -1000px;
-    cursor: crosshair;
-  }
-  body {
-    -webkit-touch-callout: none;
-    -webkit-user-select: none;
-    -khtml-user-select: none;
-    -moz-user-select: none;
-    -ms-user-select: none;
-    user-select: none;
-  }
-  </style>
-</head>
-<body>
-
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － Click and drag to select the area to be tracked</p>
-  </div>
-
-  <div id="boundingBox"></div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <video id="video" width="393" height="295" preload autoplay loop muted controls></video>
-      <canvas id="canvas" width="800" height="530"></canvas>
-  </div>
-</div>
-
-  <script>
-    (function() {
-      // BoundingBoxTracker ======================================================
-      var BoundingBoxTracker = function() {
-        BoundingBoxTracker.base(this, 'constructor');
-      };
-      tracking.inherits(BoundingBoxTracker, tracking.Tracker);
-
-      BoundingBoxTracker.prototype.templateDescriptors_ = null;
-      BoundingBoxTracker.prototype.templateKeypoints_ = null;
-      BoundingBoxTracker.prototype.fastThreshold = 60;
-      BoundingBoxTracker.prototype.blur = 3;
-
-      BoundingBoxTracker.prototype.setTemplate = function(pixels, width, height) {
-        var blur = tracking.Image.blur(pixels, width, height, 3);
-        var grayscale = tracking.Image.grayscale(blur, width, height);
-        this.templateKeypoints_ = tracking.Fast.findCorners(grayscale, width, height);
-        this.templateDescriptors_ = tracking.Brief.getDescriptors(grayscale, width, this.templateKeypoints_);
-      };
-
-      BoundingBoxTracker.prototype.track = function(pixels, width, height) {
-        var blur = tracking.Image.blur(pixels, width, height, this.blur);
-        var grayscale = tracking.Image.grayscale(blur, width, height);
-        var keypoints = tracking.Fast.findCorners(grayscale, width, height, this.fastThreshold);
-        var descriptors = tracking.Brief.getDescriptors(grayscale, width, keypoints);
-        this.emit('track', {
-          data: tracking.Brief.reciprocalMatch(this.templateKeypoints_, this.templateDescriptors_, keypoints, descriptors)
-        });
-      };
-
-      // Track ===================================================================
-      var boundingBox = document.getElementById('boundingBox');
-      var boxLeft = 403;
-      var video = document.getElementById('video');
-      var canvas = document.getElementById('canvas');
-      var canvasRect = canvas.getBoundingClientRect();
-      var context = canvas.getContext('2d');
-      var templateImageData;
-      var capturing = false;
-      var videoHeight = 295;
-      var videoWidth = 393;
-
-      var tracker = new BoundingBoxTracker();
-
-      tracker.on('track', function(event) {
-        stats.end();
-
-        if (capturing) {
-          return;
-        }
-        // Sorts best matches by confidence.
-        event.data.sort(function(a, b) {
-          return b.confidence - a.confidence;
-        });
-        // Re-draws template on canvas.
-        context.putImageData(templateImageData, boxLeft, 0);
-
-        // Plots lines connecting matches.
-        for (var i = 0; i < Math.min(10, event.data.length); i++) {
-          var template = event.data[i].keypoint1;
-          var frame = event.data[i].keypoint2;
-          context.beginPath();
-          context.strokeStyle = 'magenta';
-          context.moveTo(frame[0], frame[1]);
-          context.lineTo(boxLeft + template[0], template[1]);
-          context.stroke();
-        }
-      });
-
-      var trackerTask = tracking.track(video, tracker, { camera: true });
-      // Waits for the user to accept the camera.
-      trackerTask.stop();
-
-      // Sync video ============================================================
-      function requestFrame() {
-        window.requestAnimationFrame(function() {
-          context.clearRect(0, 0, canvas.width, canvas.height);
-          if (video.readyState === video.HAVE_ENOUGH_DATA) {
-            try {
-              context.drawImage(video, 0, 0, videoWidth, videoHeight);
-            } catch (err) {}
-          }
-          requestFrame();
-        });
-      }
-      requestFrame();
-
-      // Bounding box drag =====================================================
-      var initialPoint;
-      var left;
-      var top;
-      var width;
-      var height;
-      canvas.addEventListener('mousedown', function(event) {
-        initialPoint = [event.pageX, event.pageY];
-        capturing = true;
-      });
-      canvas.addEventListener('mousemove', function(event) {
-        if (capturing) {
-          left = Math.min(initialPoint[0], event.pageX);
-          top = Math.min(initialPoint[1], event.pageY);
-          width = Math.max(initialPoint[0], event.pageX) - left;
-          height = Math.max(initialPoint[1], event.pageY) - top;
-          boundingBox.style.display = 'block';
-          boundingBox.style.left = left + 'px';
-          boundingBox.style.top = top + 'px';
-          boundingBox.style.width = width + 'px';
-          boundingBox.style.height = height + 'px';
-        }
-      });
-      document.addEventListener('mouseup', function() {
-        boundingBox.style.display = 'none';
-        setTackerTemplate(left, top, width, height);
-        capturing = false;
-      });
-      function setTackerTemplate(left, top, width, height) {
-        templateImageData = context.getImageData(left - canvasRect.left, top - canvasRect.top, width, height);
-        canvas.width = boxLeft + width;
-        context.putImageData(templateImageData, boxLeft, 0);
-        trackerTask.stop();
-        tracker.setTemplate(templateImageData.data, width, height);
-        trackerTask.run();
-      }
-
-      // GUI Controllers
-      var gui = new dat.GUI();
-      gui.add(tracker, 'fastThreshold', 20, 100).step(5);
-      gui.add(tracker, 'blur', 1.1, 5.0).step(0.1);
-    }());
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/color_camera.html

@@ -1,65 +0,0 @@
-<!doctype html>
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - color with camera</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-  <script src="../node_modules/dat.gui/build/dat.gui.min.js"></script>
-  <script src="assets/stats.min.js"></script>
-  <script src="assets/color_camera_gui.js"></script>
-
-  <style>
-  video, canvas {
-    margin-left: 100px;
-    margin-top: 35px;
-    position: absolute;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － choose the colors you want to detect through the controls on the right</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <video id="video" width="600" height="450" preload autoplay loop muted controls></video>
-      <canvas id="canvas" width="600" height="450"></canvas>
-    </div>
-  </div>
-
-  <script>
-    window.onload = function() {
-      var video = document.getElementById('video');
-      var canvas = document.getElementById('canvas');
-      var context = canvas.getContext('2d');
-
-      var tracker = new tracking.ColorTracker();
-
-      tracking.track('#video', tracker, { camera: true });
-
-      tracker.on('track', function(event) {
-        context.clearRect(0, 0, canvas.width, canvas.height);
-
-        event.data.forEach(function(rect) {
-          if (rect.color === 'custom') {
-            rect.color = tracker.customColor;
-          }
-
-          context.strokeStyle = rect.color;
-          context.strokeRect(rect.x, rect.y, rect.width, rect.height);
-          context.font = '11px Helvetica';
-          context.fillStyle = "#fff";
-          context.fillText('x: ' + rect.x + 'px', rect.x + rect.width + 5, rect.y + 11);
-          context.fillText('y: ' + rect.y + 'px', rect.x + rect.width + 5, rect.y + 22);
-        });
-      });
-
-     initGUIControllers(tracker);
-    };
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/color_draw_something.html

@@ -1,114 +0,0 @@
-<!doctype html>
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - draw something</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking.js"></script>
-  <script src="assets/splines.min.js"></script>
-  <script src="assets/stats.min.js"></script>
-
-  <style>
-    #canvas,
-    #video {
-      height: 300px;
-      position: absolute;
-      width: 400px;
-      padding-top: 66px;
-    }
-    .draw-frame {
-      background: url(assets/draw_frame.png);
-      width: 400px;
-      height: 414px;
-      border: 1px solid #ccc;
-      top: 50%;
-      left: 50%;
-      position: absolute;
-      margin: -207px 0 0 -200px;
-    }
-
-    canvas, video {
-      -moz-transform: scale(-1, 1);
-      -o-transform: scale(-1, 1);
-      -webkit-transform: scale(-1, 1);
-      filter: FlipH;
-      transform: scale(-1, 1);
-    }
-  </style>
-</head>
-<body>
-
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － use magenta color to draw and cyan to erase</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <div class="draw-frame">
-        <video id="video" width="400" height="300" preload autoplay loop muted></video>
-        <canvas id="canvas" width="400" height="300"></canvas>
-      </div>
-    </div>
-  </div>
-
-  <script>
-    window.onload = function() {
-      var video = document.getElementById('video');
-      var canvas = document.getElementById('canvas');
-      var context = canvas.getContext('2d');
-
-      var drawSegments = [[]];
-      var segment = 0;
-
-      var tracker = new tracking.ColorTracker(['magenta', 'cyan']);
-
-      tracking.track('#video', tracker, { camera: true });
-
-      tracker.on('track', function(event) {
-        if (event.data.length === 0 && drawSegments[segment].length > 0) {
-          segment++;
-
-          if (!drawSegments[segment]) {
-            drawSegments[segment] = [];
-          }
-        }
-
-        event.data.forEach(function(rect) {
-          if (rect.color === 'magenta') {
-            draw(rect);
-          }
-          else if (rect.color === 'cyan') {
-            erase(rect);
-          }
-        });
-      });
-
-      function draw(rect) {
-        drawSegments[segment].push(rect.x + rect.width / 2, rect.y + rect.height / 2);
-      }
-
-      function erase(rect) {
-        context.clearRect(rect.x, rect.y, rect.width, rect.height);
-      }
-
-      function isInsideRect(x, y, rect) {
-        return rect.x <= x && x <= rect.x + rect.width &&
-            rect.y <= y && y <= rect.y + rect.height;
-      }
-
-      (function loop() {
-          for (var i = 0, len = drawSegments.length; i < len; i++) {
-              drawSpline(context, drawSegments[i], 0.5, false);
-          }
-
-          drawSegments = [drawSegments[drawSegments.length - 1]];
-          segment = 0;
-
-          requestAnimationFrame(loop);
-      }());
-    };
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/color_fish_tank.html

@@ -1,150 +0,0 @@
-<!doctype html>
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - color tracking fish tank</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-  <script src="../../threejs/build/three.min.js"></script>
-
-  <style>
-  body {
-    overflow: hidden;
-  }
-
-  #video, #canvas {
-    bottom: 0;
-    position: absolute;
-    z-index: 100;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － use a magenta colored object to control the scene</p>
-  </div>
-
-  <video id="video" width="320" height="240" preload autoplay loop muted></video>
-  <canvas id="canvas" width="320" height="240"></canvas>
-
-  <script>
-    var container;
-    var camera, scene, renderer, group, particle;
-    var mouseX = 0, mouseY = 0;
-    var video = document.getElementById('video');
-    var canvas = document.getElementById('canvas');
-    var context = canvas.getContext('2d');
-
-    var windowHalfX = window.innerWidth / 2;
-    var windowHalfY = window.innerHeight / 2;
-
-    init();
-    animate();
-
-    window.onload = function() {
-      var tracker = new tracking.ColorTracker();
-      tracker.setMinDimension(5);
-      tracker.setMinGroupSize(10);
-
-      tracking.track('#video', tracker, { camera: true });
-
-      tracker.on('track', onColorMove);
-    };
-
-    function init() {
-      container = document.createElement('div');
-      document.body.appendChild(container);
-
-      camera = new THREE.PerspectiveCamera(75, window.innerWidth / window.innerHeight, 1, 3000);
-      camera.position.z = 1000;
-
-      scene = new THREE.Scene();
-
-      var PI2 = Math.PI * 2;
-      var program = function (context) {
-        context.beginPath();
-        context.arc(0, 0, 0.5, 0, PI2, true);
-        context.fill();
-      }
-
-      group = new THREE.Object3D();
-      scene.add(group);
-
-      for (var i = 0; i < 1000; i++) {
-        var material = new THREE.SpriteCanvasMaterial({
-          color: Math.random() * 0x808008 + 0x808080,
-          program: program
-        });
-
-        particle = new THREE.Sprite(material);
-        particle.position.x = Math.random() * 2000 - 1000;
-        particle.position.y = Math.random() * 2000 - 1000;
-        particle.position.z = Math.random() * 2000 - 1000;
-        particle.scale.x = particle.scale.y = Math.random() * 20 + 10;
-
-        group.add(particle);
-      }
-
-      renderer = new THREE.CanvasRenderer();
-      renderer.setSize(window.innerWidth, window.innerHeight);
-      container.appendChild(renderer.domElement);
-
-      window.addEventListener('resize', onWindowResize, false);
-    }
-
-    function onWindowResize() {
-      windowHalfX = window.innerWidth / 2;
-      windowHalfY = window.innerHeight / 2;
-
-      camera.aspect = window.innerWidth / window.innerHeight;
-      camera.updateProjectionMatrix();
-
-      renderer.setSize(window.innerWidth, window.innerHeight);
-    }
-
-    function onColorMove(event) {
-      if (event.data.length === 0) {
-        return;
-      }
-
-      var maxRect;
-      var maxRectArea = 0;
-
-      event.data.forEach(function(rect) {
-        if (rect.width * rect.height > maxRectArea){
-          maxRectArea = rect.width * rect.height;
-          maxRect = rect;
-        }
-      });
-
-      if (maxRectArea > 0) {
-        var rectCenterX = maxRect.x + (maxRect.width/2);
-        var rectCenterY = maxRect.y + (maxRect.height/2);
-        mouseX = (rectCenterX - 160) * (window.innerWidth/320) * 10;
-        mouseY = (rectCenterY - 120) * (window.innerHeight/240) * 10;
-
-        context.clearRect(0, 0, canvas.width, canvas.height);
-        context.strokeStyle = maxRect.color;
-        context.strokeRect(maxRect.x, maxRect.y, maxRect.width, maxRect.height);
-        context.font = '11px Helvetica';
-        context.fillStyle = "#fff";
-        context.fillText('x: ' + maxRect.x + 'px', maxRect.x + maxRect.width + 5, maxRect.y + 11);
-        context.fillText('y: ' + maxRect.y + 'px', maxRect.x + maxRect.width + 5, maxRect.y + 22);
-      }
-    }
-
-    function animate() {
-      window.requestAnimationFrame(animate);
-      render();
-    }
-
-    function render() {
-      camera.position.x += (mouseX - camera.position.x) * 0.05;
-      camera.position.y += (- mouseY - camera.position.y) * 0.05;
-      camera.lookAt(scene.position);
-      renderer.render(scene, camera);
-    }
-  </script>
-</body>
-</html>

common/tracking.js/examples/color_hello_world.html

@@ -1,60 +0,0 @@
-<!doctype html>
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - color hello world</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-
-  <style>
-  .rect {
-    width: 80px;
-    height: 80px;
-    position: absolute;
-    left: -1000px;
-    top: -1000px;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － detect certain colors in a image</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <img id="img" src="assets/psmove.png" />
-    </div>
-  </div>
-
-  <script>
-    window.onload = function() {
-      var img = document.getElementById('img');
-      var demoContainer = document.querySelector('.demo-container');
-
-      var tracker = new tracking.ColorTracker(['magenta', 'cyan', 'yellow']);
-
-      tracker.on('track', function(event) {
-        event.data.forEach(function(rect) {
-          window.plot(rect.x, rect.y, rect.width, rect.height, rect.color);
-        });
-      });
-
-      tracking.track('#img', tracker);
-
-      window.plot = function(x, y, w, h, color) {
-        var rect = document.createElement('div');
-        document.querySelector('.demo-container').appendChild(rect);
-        rect.classList.add('rect');
-        rect.style.border = '2px solid ' + color;
-        rect.style.width = w + 'px';
-        rect.style.height = h + 'px';
-        rect.style.left = (img.offsetLeft + x) + 'px';
-        rect.style.top = (img.offsetTop + y) + 'px';
-      };
-    };
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/color_video.html

@@ -1,82 +0,0 @@
-<!doctype html>
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - color with video</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-   <script src="../node_modules/dat.gui/build/dat.gui.min.js"></script>
-  <script src="assets/stats.min.js"></script>
-  <script src="assets/color_camera_gui.js"></script>
-
-  <style>
-  .demo-container {
-    background-color: black;
-  }
-
-  video, canvas {
-    position: absolute;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － detect certain colors in a video</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <div id="rectangle"></div>
-      <video id="video" width="800" height="530" preload autoplay loop muted controls>
-        <source src="assets/minions.mp4" type="video/mp4">
-        <source src="assets/minions.ogv" type="video/ogg">
-      </video>
-      <canvas id="canvas" width="800" height="500"></canvas>
-    </div>
-  </div>
-
-  <script>
-    window.onload = function() {
-      var canvas = document.getElementById('canvas');
-      var context = canvas.getContext('2d');
-
-      tracking.ColorTracker.registerColor('purple', function(r, g, b) {
-        var dx = r - 120;
-        var dy = g - 60;
-        var dz = b - 210;
-
-        if ((b - g) >= 100 && (r - g) >= 60) {
-          return true;
-        }
-        return dx * dx + dy * dy + dz * dz < 3500;
-      });
-
-      var tracker = new tracking.ColorTracker(['yellow', 'purple']);
-      tracker.setMinDimension(5);
-
-      tracking.track('#video', tracker);
-
-      tracker.on('track', function(event) {
-        context.clearRect(0, 0, canvas.width, canvas.height);
-
-        event.data.forEach(function(rect) {
-          if (rect.color === 'custom') {
-            rect.color = tracker.customColor;
-          }
-
-          context.strokeStyle = rect.color;
-          context.strokeRect(rect.x, rect.y, rect.width, rect.height);
-          context.font = '11px Helvetica';
-          context.fillStyle = "#fff";
-          context.fillText('x: ' + rect.x + 'px', rect.x + rect.width + 5, rect.y + 11);
-          context.fillText('y: ' + rect.y + 'px', rect.x + rect.width + 5, rect.y + 22);
-        });
-      });
-
-      initGUIControllers(tracker);
-    };
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/face_alignment_image.html

@@ -1,100 +0,0 @@
-<!doctype html>
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - face alignment with images</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking.js"></script>
-  <script src="../build/data/face-min.js"></script>
-  <script src="../src/alignment/training/Landmarks.js"></script>
-  <script src="../src/alignment/training/Regressor.js"></script>
-  
-  <script src="../node_modules/dat.gui/build/dat.gui.min.js"></script>
-  <script src="assets/stats.min.js"></script>
-
-  <style>
-  .rect, .circle {
-    left: -1000px;
-    position: absolute;
-    top: -1000px;
-  }
-  .rect{
-    border: 2px solid #a64ceb;
-  }
-  .circle {
-    border-radius: 50%;
-    box-shadow: 0px 0px 3px rgba(0,0,0,0.3);
-  }
-  #img {
-    position: absolute;
-    top: 50%;
-    left: 50%;
-    margin: -200px 0 0 -200px;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － align face landmarks to images</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <img id="img" src="assets/emilia.jpg" />
-    </div>
-  </div>
-
-  <script>
-    window.onload = function() {
-      var img = document.getElementById('img');
-
-      var tracker = new tracking.LandmarksTracker();
-      tracker.setInitialScale(4);
-      tracker.setStepSize(2);
-      tracker.setEdgesDensity(0.1);
-
-      tracking.track('#img', tracker);
-
-      tracker.on('track', function(event) {
-
-        if(!event.data) return;
-
-        event.data.faces.forEach(function(rect) {
-          window.plot(rect.x, rect.y, rect.width, rect.height);
-        });
-
-        event.data.landmarks.forEach(function(landmarks) {
-          for(var i=0; i < landmarks.length; i++){
-            window.plotLandmark(landmarks[i][0], landmarks[i][1], 2, '#44ABDA');
-          }
-        });
-
-      });
-
-      window.plot = function(x, y, w, h) {
-        var rect = document.createElement('div');
-        document.querySelector('.demo-container').appendChild(rect);
-        rect.classList.add('rect');
-        rect.style.width = w + 'px';
-        rect.style.height = h + 'px';
-        rect.style.left = (img.offsetLeft + x) + 'px';
-        rect.style.top = (img.offsetTop + y) + 'px';
-      };
-
-      window.plotLandmark = function(x,y, radius, color){
-        var circle = document.createElement('div');
-        document.querySelector('.demo-container').appendChild(circle);
-        circle.classList.add('circle');
-        circle.style.backgroundColor = color;
-        circle.style.width = (radius*2) + 'px';
-        circle.style.height = (radius*2) + 'px';
-        circle.style.left = (img.offsetLeft + x) + 'px';
-        circle.style.top = (img.offsetTop + y) + 'px';
-      }
-
-    };
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/face_alignment_video.html

@@ -1,84 +0,0 @@
-<!doctype html>
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - face alignment with camera</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking.js"></script>
-  <script src="../build/data/face-min.js"></script>
-  <script src="../src/alignment/training/Landmarks.js"></script>
-  <script src="../src/alignment/training/Regressor.js"></script>
-
-  <script src="../node_modules/dat.gui/build/dat.gui.min.js"></script>
-  <script src="assets/stats.min.js"></script>
-
-  <style>
-  video, canvas {
-    margin-left: 230px;
-    margin-top: 120px;
-    position: absolute;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － get user's webcam and align face landmarks to detected faces</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <video id="video" width="320" height="240" src="assets/franck.mp4" preload autoplay loop muted></video>
-      <canvas id="canvas" width="320" height="240"></canvas>
-    </div>
-  </div>
-
-  <script>
-    window.onload = function() {
-      var video = document.getElementById('video');
-      var canvas = document.getElementById('canvas');
-      var context = canvas.getContext('2d');
-
-      var tracker = new tracking.LandmarksTracker();
-      tracker.setInitialScale(4);
-      tracker.setStepSize(2);
-      tracker.setEdgesDensity(0.1);
-
-      tracking.track('#video', tracker);
-
-      tracker.on('track', function(event) {
-
-        context.clearRect(0,0,canvas.width, canvas.height);
-
-        if(!event.data) return;
-
-          event.data.faces.forEach(function(rect) {
-            context.strokeStyle = '#a64ceb';
-            context.strokeRect(rect.x, rect.y, rect.width, rect.height);
-            context.font = '11px Helvetica';
-            context.fillStyle = "#fff";
-            context.fillText('x: ' + rect.x + 'px', rect.x + rect.width + 5, rect.y + 11);
-            context.fillText('y: ' + rect.y + 'px', rect.x + rect.width + 5, rect.y + 22);
-          });
-
-          event.data.landmarks.forEach(function(landmarks) {
-            for(var l in landmarks){
-              context.beginPath();
-              context.fillStyle = "#fff";
-              context.arc(landmarks[l][0],landmarks[l][1],1,0,2*Math.PI);
-              context.fill();
-            }
-          });
-
-      });
-
-      var gui = new dat.GUI();
-      gui.add(tracker, 'edgesDensity', 0.1, 0.5).step(0.01).listen();
-      gui.add(tracker, 'initialScale', 1.0, 10.0).step(0.1).listen();
-      gui.add(tracker, 'stepSize', 1, 5).step(0.1).listen();
-
-    };
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/face_alignment_webcam.html

@@ -1,229 +0,0 @@
-<!doctype html>
-<html>
-<head>
-        <meta charset="utf-8">
-        <title>tracking.js - face alignment with camera</title>
-        <!-- here is the frame around each example - to be removed - to a fullscreen video - working on mobile too -->
-        <!-- <link rel="stylesheet" href="assets/demo.css"> -->
-        
-        <script src="../build/tracking.js"></script>
-        <script src="../build/data/face-min.js"></script>
-        <script src="../src/alignment/training/Landmarks.js"></script>
-        <script src="../src/alignment/training/Regressor.js"></script>
-        
-        <script src="../node_modules/dat.gui/build/dat.gui.min.js"></script>
-</head>
-<body>
-        <style>
-                #videoWebcam {
-                        position: absolute;
-                        top: 0px;
-                        left: 0px;
-                        width : 320px;
-                        height: auto;
-                        zoom: 3;
-                }
-                #canvasDetection {
-                        position: absolute;
-                        top: 0px;
-                        left: 0px;
-                        width : 320px;
-                        height: auto;
-                        zoom: 3;
-                }
-        </style>
-	<video id="videoWebcam" width="368" height="288" autoplay loop>
-		<source src="./assets/franck.mp4" type="video/mp4"/>
-		<source src="./assets/franck.ogv" type="video/ogg"/>
-	</video>
-        <!-- <video id="videoWebcam" preload autoplay loop muted></video> -->
-        <canvas id="canvasDetection"></canvas>
-        
-<script>
-        var canvasDetection = document.querySelector('#canvasDetection');
-        canvasDetection.width = 320
-        canvasDetection.height = 240
-        var context = canvasDetection.getContext('2d');
-
-        // tracking.LBF.maxNumStages = 10
-        var tracker = new tracking.LandmarksTracker();
-        tracker.setEdgesDensity(0.1);
-        tracker.setInitialScale(4);
-        tracker.setStepSize(2);
-
-        tracker.setInitialScale(2);
-        tracker.setStepSize(1);
-
-        
-        var gui = new dat.GUI();
-        gui.add(tracker, 'edgesDensity', 0.1, 0.5).step(0.01).listen();
-        gui.add(tracker, 'initialScale', 1.0, 10.0).step(0.1).listen();
-        gui.add(tracker, 'stepSize', 0.5, 5).step(0.1).listen();
-        
-
-        var videoElement = document.querySelector('#videoWebcam')
-        tracking.track(videoElement, tracker);
-        // tracking.track(videoElement, tracker, { camera: true });
-        
-        var landmarksPerFace = 30
-        var landmarkFeatures = {
-                jaw : {
-                        first: 0,
-                        last: 8,
-                        fillStyle: 'white',
-                        closed: false,
-                },
-                nose : {
-                        first:15,
-                        last: 18,
-                        fillStyle: 'green',
-                        closed: true,
-                },
-                mouth : {
-                        first:27,
-                        last: 30,
-                        fillStyle: 'red',
-                        closed: true,
-                },
-                eyeL : {
-                        first:19,
-                        last: 22,
-                        fillStyle: 'purple',
-                        closed: false,
-                },
-                eyeR : {
-                        first:23,
-                        last: 26,
-                        fillStyle: 'purple',
-                        closed: false,
-                },
-                eyeBrowL : {
-                        first: 9,
-                        last: 11,
-                        fillStyle: 'yellow',
-                        closed: false,
-                },
-                eyeBrowR : {
-                        first:12,
-                        last: 14,
-                        fillStyle: 'yellow',
-                        closed: false,
-                },
-        }
-
-        //////////////////////////////////////////////////////////////////////////////
-        //                Code Separator
-        //////////////////////////////////////////////////////////////////////////////
-        var parameters = {
-                landmarkLerpFactor : 0.7,
-                boundinBoxVisible : true,
-                jawVisible : true,
-                eyeBrowLVisible : true,
-                eyeBrowRVisible : true,
-                noseVisible : true,
-                eyeLVisible : true,
-                eyeRVisible : true,
-                mouthVisible : true,
-        }
-        gui.add(parameters, 'landmarkLerpFactor', 0.0, 1).listen().name('Landmarks Lerp');
-        gui.add(parameters, 'boundinBoxVisible', 0.0, 1).listen().name('bounding box');
-        Object.keys(landmarkFeatures).forEach(function(featureLabel){
-                gui.add(parameters, featureLabel + 'Visible').listen().name(featureLabel);
-        })
-
-        var lerpedFacesLandmarks = []
-        
-        tracker.on('track', function(event) {
-                // clear debug canvasDetection
-                context.clearRect(0,0,canvasDetection.width, canvasDetection.height);
-
-                if( event.data === undefined ) return;
-                
-                event.data.faces.forEach(function(boundingBox, faceIndex) {
-                        var faceLandmarks = event.data.landmarks[faceIndex]
-
-                        if( parameters.boundinBoxVisible === true ) displayFaceLandmarksBoundingBox(boundingBox, faceIndex)
-
-                        // lerpFacesLandmarks
-                        lerpFacesLandmarks(faceLandmarks)
-                        
-                        // display each faceLandmarks
-                        displayFaceLandmarksDot(lerpedFacesLandmarks)
-                });
-        })
-
-        function lerpFacesLandmarks(newFaceLandmarks){
-                // init lerpFacesLandmarks if needed
-                for(var i = 0; i < newFaceLandmarks.length; i++){
-                        if( lerpedFacesLandmarks[i] !== undefined ) continue
-                        lerpedFacesLandmarks[i] = [
-                                newFaceLandmarks[i][0],
-                                newFaceLandmarks[i][1],
-                        ]                        
-                }
-
-                // init lerpFacesLandmarks if needed
-                for(var i = 0; i < newFaceLandmarks.length; i++){
-                        var lerpFactor = parameters.landmarkLerpFactor
-                        lerpedFacesLandmarks[i][0] = newFaceLandmarks[i][0] * lerpFactor  + lerpedFacesLandmarks[i][0] * (1-lerpFactor)
-                        lerpedFacesLandmarks[i][1] = newFaceLandmarks[i][1] * lerpFactor  + lerpedFacesLandmarks[i][1] * (1-lerpFactor)
-                }
-        }
-
-        //////////////////////////////////////////////////////////////////////////////
-        //                Code Separator
-        //////////////////////////////////////////////////////////////////////////////
-        function displayFaceLandmarksBoundingBox(boundingBox, faceIndex){
-                // display the box
-                context.strokeStyle = '#a64ceb';
-                context.strokeRect(boundingBox.x, boundingBox.y, boundingBox.width, boundingBox.height);
-
-                // display the size of the box
-                context.font = '11px Helvetica';
-                context.fillStyle = "#fff";
-                context.fillText('idx: '+faceIndex, boundingBox.x + boundingBox.width + 5, boundingBox.y + 11);
-                context.fillText('x: ' + boundingBox.x + 'px', boundingBox.x + boundingBox.width + 5, boundingBox.y + 22);
-                context.fillText('y: ' + boundingBox.y + 'px', boundingBox.x + boundingBox.width + 5, boundingBox.y + 33);
-        }
-        
-        function displayFaceLandmarksDot(faceLandmarks){
-                Object.keys(landmarkFeatures).forEach(function(featureLabel){
-                        if( parameters[featureLabel+'Visible'] === false )      return
-                        displayFaceLandmarksFeature(faceLandmarks, featureLabel)
-                })
-        }
-        function displayFaceLandmarksFeature(faceLandmarks, featureLabel){
-                var feature = landmarkFeatures[featureLabel]
-                
-                // draw dots
-                context.fillStyle = feature.fillStyle
-                for(var i = feature.first; i <= feature.last; i++){
-                        var xy = faceLandmarks[i]
-                        context.beginPath();
-                        context.arc(xy[0],xy[1],1,0,2*Math.PI);
-                        context.fill();                                
-                }                
-                
-                // draw lines
-                var feature = landmarkFeatures[featureLabel]
-                context.strokeStyle = feature.fillStyle
-                context.beginPath();
-                for(var i = feature.first; i <= feature.last; i++){
-                        var x = faceLandmarks[i][0]
-                        var y = faceLandmarks[i][1]
-                        if( i === 0 ){
-                                context.moveTo(x, y)
-                        }else{
-                                context.lineTo(x, y)
-                        }
-                }                
-                if( feature.closed === true ){
-                        var x = faceLandmarks[feature.first][0]
-                        var y = faceLandmarks[feature.first][1]
-                        context.lineTo(x, y)
-                }
-
-                context.stroke();
-
-        }
-</script></body>

common/tracking.js/examples/face_camera.html

@@ -1,67 +0,0 @@
-<!doctype html>
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - face with camera</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-  <script src="../build/data/face-min.js"></script>
-   <script src="../node_modules/dat.gui/build/dat.gui.min.js"></script>
-  <script src="assets/stats.min.js"></script>
-
-  <style>
-  video, canvas {
-    margin-left: 230px;
-    margin-top: 120px;
-    position: absolute;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － get user's webcam and detect faces</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <video id="video" width="320" height="240" preload autoplay loop muted></video>
-      <canvas id="canvas" width="320" height="240"></canvas>
-    </div>
-  </div>
-
-  <script>
-    window.onload = function() {
-      var video = document.getElementById('video');
-      var canvas = document.getElementById('canvas');
-      var context = canvas.getContext('2d');
-
-      var tracker = new tracking.ObjectTracker('face');
-      tracker.setInitialScale(4);
-      tracker.setStepSize(2);
-      tracker.setEdgesDensity(0.1);
-
-      tracking.track('#video', tracker, { camera: true });
-
-      tracker.on('track', function(event) {
-        context.clearRect(0, 0, canvas.width, canvas.height);
-
-        event.data.forEach(function(rect) {
-          context.strokeStyle = '#a64ceb';
-          context.strokeRect(rect.x, rect.y, rect.width, rect.height);
-          context.font = '11px Helvetica';
-          context.fillStyle = "#fff";
-          context.fillText('x: ' + rect.x + 'px', rect.x + rect.width + 5, rect.y + 11);
-          context.fillText('y: ' + rect.y + 'px', rect.x + rect.width + 5, rect.y + 22);
-        });
-      });
-
-      var gui = new dat.GUI();
-      gui.add(tracker, 'edgesDensity', 0.1, 0.5).step(0.01);
-      gui.add(tracker, 'initialScale', 1.0, 10.0).step(0.1);
-      gui.add(tracker, 'stepSize', 1, 5).step(0.1);
-    };
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/face_fish_tank.html

@@ -1,89 +0,0 @@
-<!doctype html>
-<html lang="en">
-<head>
-  <meta charset="utf-8">
-  <meta name="viewport" content="width=device-width, user-scalable=no, minimum-scale=1.0, maximum-scale=1.0">
-  <title>tracking.js - face tracking fish tank</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-  <script src="../build/data/face-min.js"></script>
-  <script src="../../threejs/build/three.min.js"></script>
-  <script src="assets/fish_tank/FishTankRenderer.js"></script>
-
-  <style>
-  body {
-    overflow: hidden;
-  }
-
-  #video, #canvas {
-    bottom: 0;
-    position: absolute;
-    z-index: 100;
-  }
-
-  #viewport {
-    padding-top: 40px;
-  }
-  </style>
-</head>
-
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － get user's webcam and detect faces to control the scene</p>
-  </div>
-
-  <div id="viewport">
-    <video id="video" width="320" height="240" preload autoplay loop muted></video>
-    <canvas id="canvas" width="320" height="240"></canvas>
-  </div>
-
-  <script>
-    var viewport = document.getElementById('viewport');
-    var canvas = document.getElementById('canvas');
-    var context = canvas.getContext('2d');
-
-    var fishTankRenderer = new FishTankRenderer();
-    fishTankRenderer.init(viewport);
-
-    var faceX = 0;
-    var faceY = 0;
-
-    var tracker = new tracking.ObjectTracker('face');
-    tracker.setInitialScale(4);
-    tracker.setStepSize(2);
-
-    tracking.track('#video', tracker, { camera: true });
-
-    tracker.on('track', function(event) {
-      var maxRectArea = 0;
-      var maxRect;
-
-      event.data.forEach(function(rect) {
-        if (rect.width * rect.height > maxRectArea){
-          maxRectArea = rect.width * rect.height;
-          maxRect = rect;
-        }
-
-        context.clearRect(0, 0, canvas.width, canvas.height);
-        context.strokeStyle = 'magenta';
-        context.strokeRect(rect.x, rect.y, rect.width, rect.height);
-        context.font = '11px Helvetica';
-        context.fillStyle = "#fff";
-        context.fillText('x: ' + rect.x + 'px', rect.x + rect.width + 5, rect.y + 11);
-        context.fillText('y: ' + rect.y + 'px', rect.x + rect.width + 5, rect.y + 22);
-      });
-
-      if(maxRectArea > 0) {
-        var rectCenterX = maxRect.x + (maxRect.width/2);
-        var rectCenterY = maxRect.y + (maxRect.height/2);
-        faceX = (rectCenterX - 160) * (window.innerWidth/320) * 50;
-        faceY = (rectCenterY - 120) * (window.innerHeight/240) * 50;
-      }
-
-      fishTankRenderer.render(faceX, faceY);
-    });
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/face_hello_world.html

@@ -1,68 +0,0 @@
-<!doctype html>
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - face hello world</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-  <script src="../build/data/face-min.js"></script>
-  <script src="../build/data/eye-min.js"></script>
-  <script src="../build/data/mouth-min.js"></script>
-
-  <style>
-  .rect {
-    border: 2px solid #a64ceb;
-    left: -1000px;
-    position: absolute;
-    top: -1000px;
-  }
-
-  #img {
-    position: absolute;
-    top: 50%;
-    left: 50%;
-    margin: -173px 0 0 -300px;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － detect faces, eyes and mouths in a image</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <img id="img" src="assets/faces.jpg" />
-    </div>
-  </div>
-
-  <script>
-    window.onload = function() {
-      var img = document.getElementById('img');
-
-      var tracker = new tracking.ObjectTracker(['face', 'eye', 'mouth']);
-      tracker.setStepSize(1.7);
-
-      tracking.track('#img', tracker);
-
-      tracker.on('track', function(event) {
-        event.data.forEach(function(rect) {
-          window.plot(rect.x, rect.y, rect.width, rect.height);
-        });
-      });
-
-      window.plot = function(x, y, w, h) {
-        var rect = document.createElement('div');
-        document.querySelector('.demo-container').appendChild(rect);
-        rect.classList.add('rect');
-        rect.style.width = w + 'px';
-        rect.style.height = h + 'px';
-        rect.style.left = (img.offsetLeft + x) + 'px';
-        rect.style.top = (img.offsetTop + y) + 'px';
-      };
-    };
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/face_tag_friends.html

@@ -1,123 +0,0 @@
-<!doctype html>
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - tag friends</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-  <script src="../build/data/face-min.js"></script>
-
-  <style>
-  #photo:hover .rect {
-    opacity: .75;
-    transition: opacity .75s ease-out;
-  }
-
-  .rect:hover * {
-    opacity: 1;
-  }
-
-  .rect {
-    border-radius: 2px;
-    border: 3px solid white;
-    box-shadow: 0 16px 28px 0 rgba(0, 0, 0, 0.3);
-    cursor: pointer;
-    left: -1000px;
-    opacity: 0;
-    position: absolute;
-    top: -1000px;
-  }
-
-  .arrow {
-    border-bottom: 10px solid white;
-    border-left: 10px solid transparent;
-    border-right: 10px solid transparent;
-    height: 0;
-    width: 0;
-    position: absolute;
-    left: 50%;
-    margin-left: -5px;
-    bottom: -12px;
-    opacity: 0;
-  }
-
-  input {
-    border: 0px;
-    bottom: -42px;
-    color: #a64ceb;
-    font-size: 15px;
-    height: 30px;
-    left: 50%;
-    margin-left: -90px;
-    opacity: 0;
-    outline: none;
-    position: absolute;
-    text-align: center;
-    width: 180px;
-    transition: opacity .35s ease-out;
-  }
-
-  #img {
-    position: absolute;
-    top: 50%;
-    left: 50%;
-    margin: -173px 0 0 -300px;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － hover image to see all faces detected</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <span id="photo"><img id="img" src="assets/faces.jpg" /></span>
-    </div>
-  </div>
-
-  <script>
-    window.onload = function() {
-      var img = document.getElementById('img');
-
-      var tracker = new tracking.ObjectTracker('face');
-
-      tracking.track(img, tracker);
-
-      tracker.on('track', function(event) {
-        event.data.forEach(function(rect) {
-          plotRectangle(rect.x, rect.y, rect.width, rect.height);
-        });
-      });
-
-      var friends = [ 'Thomas Middleditch', 'Martin Starr', 'Zach Woods' ];
-
-      var plotRectangle = function(x, y, w, h) {
-        var rect = document.createElement('div');
-        var arrow = document.createElement('div');
-        var input = document.createElement('input');
-
-        input.value = friends.pop();
-
-        rect.onclick = function name() {
-          input.select();
-        };
-
-        arrow.classList.add('arrow');
-        rect.classList.add('rect');
-
-        rect.appendChild(input);
-        rect.appendChild(arrow);
-        document.getElementById('photo').appendChild(rect);
-
-        rect.style.width = w + 'px';
-        rect.style.height = h + 'px';
-        rect.style.left = (img.offsetLeft + x) + 'px';
-        rect.style.top = (img.offsetTop + y) + 'px';
-      };
-    };
-  </script>
-
-</body>
-</html>

common/tracking.js/examples/fast.html

@@ -1,73 +0,0 @@
-<!doctype html>
-
-<html>
-<head>
-  <meta charset="utf-8">
-  <title>tracking.js - feature detection</title>
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-   <script src="../node_modules/dat.gui/build/dat.gui.min.js"></script>
-
-  <style>
-  .demo-container {
-    background: #131112;
-  }
-  #image {
-    position: absolute;
-    left: -1000px;
-    top: -1000px;
-  }
-  #canvas {
-    position: absolute;
-    left: 50%;
-    top: 50%;
-    margin: -200px 0 0 -200px;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － detect feature points on a image</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <img id="image" src="assets/fast.png" />
-      <canvas id="canvas" width="400" height="400"></canvas>
-    </div>
-  </div>
-
-  <script>
-    window.onload = function() {
-      var width = 400;
-      var height = 400;
-      var canvas = document.getElementById('canvas');
-      var context = canvas.getContext('2d');
-
-      var image = document.getElementById('image');
-
-      window.fastThreshold = 10;
-
-      var doFindFeatures = function() {
-        tracking.Fast.THRESHOLD = window.fastThreshold;
-        context.drawImage(image, 0, 0, width, height);
-
-        var imageData = context.getImageData(0, 0, width, height);
-        var gray = tracking.Image.grayscale(imageData.data, width, height);
-        var corners = tracking.Fast.findCorners(gray, width, height);
-
-        for (var i = 0; i < corners.length; i += 2) {
-          context.fillStyle = '#f00';
-          context.fillRect(corners[i], corners[i + 1], 3, 3);
-        }
-      };
-
-      doFindFeatures();
-
-      var gui = new dat.GUI();
-      gui.add(window, 'fastThreshold', 0, 100).onChange(doFindFeatures);
-    }
-  </script>
-</body>
-</html>

common/tracking.js/examples/fast_camera.html

@@ -1,85 +0,0 @@
-<!doctype html>
-
-<html>
-<head>
-  <title>tracking.js -  feature detector with camera</title>
-
-  <meta charset="utf-8">
-  <link rel="stylesheet" href="assets/demo.css">
-
-  <script src="../build/tracking-min.js"></script>
-  <script src="../node_modules/dat.gui/build/dat.gui.min.js"></script>
-  <script src="assets/stats.min.js"></script>
-
-  <style>
-  #video {
-    position: absolute;
-    top: -1000px;
-  }
-
-  #canvas {
-    left: 50%;
-    top: 50%;
-    margin-left: -200px;
-    margin-top: -150px;
-    position: absolute;
-  }
-  </style>
-</head>
-<body>
-  <div class="demo-title">
-    <p><a href="http://trackingjs.com" target="_parent">tracking.js</a> － display detected features</p>
-  </div>
-
-  <div class="demo-frame">
-    <div class="demo-container">
-      <video id="video" width="400" height="300" preload autoplay loop muted></video>
-      <canvas id="canvas" width="400" height="300"></canvas>
-    </div>
-  </div>
-
-  <script>
-    var canvas = document.getElementById('canvas');
-    var context = canvas.getContext('2d');
-
-    var FastTracker = function() {
-      FastTracker.base(this, 'constructor');
-    };
-    tracking.inherits(FastTracker, tracking.Tracker);
-
-    tracking.Fast.THRESHOLD = 2;
-    FastTracker.prototype.threshold = tracking.Fast.THRESHOLD;
-
-    FastTracker.prototype.track = function(pixels, width, height) {
-      stats.begin();
-      var gray = tracking.Image.grayscale(pixels, width, height);
-      var corners = tracking.Fast.findCorners(gray, width, height);
-      stats.end();
-
-      this.emit('track', {
-        data: corners
-      });
-    };
-
-    var tracker = new FastTracker();
-
-    tracker.on('track', function(event) {
-      context.clearRect(0, 0, canvas.width, canvas.height);
-      var corners = event.data;
-      for (var i = 0; i < corners.length; i += 2) {
-        context.fillStyle = '#f00';
-        context.fillRect(corners[i], corners[i + 1], 2, 2);
-      }
-    });
-
-    tracking.track('#video', tracker, { camera: true });
-
-    // GUI Controllers
-    var gui = new dat.GUI();
-
-    gui.add(tracker, 'threshold', 1, 100).onChange(function(value) {
-      tracking.Fast.THRESHOLD = value;
-    });
-  </script>
-</body>
-</html>

common/tracking.js/gulpfile.js

@@ -1,118 +0,0 @@
-'use strict';
-var gulp = require('gulp');
-var concat = require('gulp-concat');
-var header = require('gulp-header');
-var jsdoc = require('gulp-jsdoc');
-var jshint = require('gulp-jshint');
-var nodeunit = require('gulp-nodeunit');
-var pkg = require('./package.json');
-var rename = require('gulp-rename');
-var rimraf = require('gulp-rimraf');
-var stylish = require('jshint-stylish');
-var uglify = require('gulp-uglify');
-var esformatter = require('gulp-esformatter');
-var runSequence = require('run-sequence');
-
-gulp.task('all', ['clean'], function() {
-  return runSequence(['build', 'build-data']);
-});
-
-gulp.task('clean', function() {
-  return gulp.src('build').pipe(rimraf());
-});
-
-gulp.task('build', function() {
-  var files = [
-    'src/tracking.js',
-    'src/utils/EventEmitter.js',
-    'src/utils/Canvas.js',
-    'src/utils/DisjointSet.js',
-    'src/utils/Image.js',
-    'src/detection/ViolaJones.js',
-    'src/features/Brief.js',
-    'src/features/Fast.js',
-    'src/math/Math.js',
-    'src/math/Matrix.js',
-    'src/pose/EPnP.js',
-    'src/trackers/Tracker.js',
-    'src/trackers/TrackerTask.js',
-    'src/trackers/ColorTracker.js',
-    'src/trackers/ObjectTracker.js',
-    'src/trackers/LandmarksTracker.js',
-    'src/alignment/Regressor.js',
-    'src/alignment/LBF.js'
-  ];
-
-  return gulp.src(files)
-    .pipe(concat('tracking.js'))
-    .pipe(banner())
-    .pipe(gulp.dest('build'))
-    .pipe(uglify())
-    .pipe(rename({
-      suffix: '-min'
-    }))
-    .pipe(banner())
-    .pipe(gulp.dest('build'));
-});
-
-gulp.task('build-data', function() {
-  return gulp.src('src/detection/training/haar/**.js')
-    .pipe(banner())
-    .pipe(gulp.dest('build/data'))
-    .pipe(rename({
-      suffix: '-min'
-    }))
-    .pipe(uglify())
-    .pipe(banner())
-    .pipe(gulp.dest('build/data'));
-});
-
-gulp.task('docs', function() {
-  return gulp.src(['src/**/*.js', 'README.md'])
-    .pipe(jsdoc('docs'));
-});
-
-gulp.task('format', function() {
-  return gulp.src(['src/**/*.js', '!src/detection/training/**/*.js'])
-    .pipe(esformatter())
-    .pipe(gulp.dest('src'));
-});
-
-gulp.task('lint', function() {
-  return gulp.src('src/**/**.js')
-    .pipe(jshint())
-    .pipe(jshint.reporter(stylish));
-});
-
-gulp.task('test', function(cb) {
-  gulp.src('test/*.js')
-    .pipe(nodeunit())
-    .on('end', cb);
-});
-
-gulp.task('test-watch', function() {
-  return gulp.watch(['src/**/*.js', 'test/**/*.js'], ['test']);
-});
-
-gulp.task('watch', function() {
-  gulp.watch('src/**/*.js', ['build']);
-  gulp.watch('src/data/*.js', ['build-data']);
-});
-
-// Private helpers
-// ===============
-
-function banner() {
-  var stamp = [
-    '/**',
-    ' * <%= pkg.name %> - <%= pkg.description %>',
-    ' * @author <%= pkg.author.name %> <<%= pkg.author.email %>>',
-    ' * @version v<%= pkg.version %>',
-    ' * @link <%= pkg.homepage %>',
-    ' * @license <%= pkg.license %>',
-    ' */',
-    ''
-  ].join('\n');
-
-  return header(stamp, { pkg: pkg });
-}

common/tracking.js/package.json

@@ -1,45 +0,0 @@
-{
-  "name": "tracking",
-  "version": "1.1.3",
-  "main": "build/tracking.js",
-  "description": "A modern approach for Computer Vision on the web.",
-  "homepage": "http://trackingjs.com",
-  "keywords": [
-    "tracking",
-    "trackingjs",
-    "webrtc"
-  ],
-  "author": {
-    "name": "Eduardo Lundgren",
-    "email": "edu@rdo.io",
-    "web": "http://eduardo.io",
-    "twitter": "eduardolundgren"
-  },
-  "repository": {
-    "type": "git",
-    "url": "git@github.com:eduardolundgren/tracking.js.git"
-  },
-  "scripts": {
-    "test": "gulp test",
-    "build": "gulp build"
-  },
-  "license": "BSD",
-  "devDependencies": {
-    "gulp": "^3.9.0",
-    "gulp-concat": "^2.6.0",
-    "gulp-esformatter": "^5.0.0",
-    "gulp-header": "^1.7.1",
-    "gulp-jsdoc": "^0.1.5",
-    "gulp-jshint": "^2.0.0",
-    "gulp-nodeunit": "0.0.5",
-    "gulp-rename": "^1.2.2",
-    "gulp-rimraf": "^0.2.0",
-    "gulp-uglify": "^1.5.1",
-    "jshint": "^2.8.0",
-    "jshint-stylish": "^2.1.0",
-    "nodeunit": "^0.9.1",
-    "png-js": "^0.1.1",
-    "run-sequence": "^1.1.5",
-    "dat.gui": "^0.6.1"
-  }
-}

common/tracking.js/src/alignment/LBF.js

@@ -1,222 +0,0 @@
-(function() {
-  /**
-   * Face Alignment via Regressing Local Binary Features (LBF)
-   * This approach has two components: a set of local binary features and
-   * a locality principle for learning those features.
-   * The locality principle is used to guide the learning of a set of highly
-   * discriminative local binary features for each landmark independently.
-   * The obtained local binary features are used to learn a linear regression
-   * that later will be used to guide the landmarks in the alignment phase.
-   * 
-   * @authors: VoxarLabs Team (http://cin.ufpe.br/~voxarlabs)
-   *           Lucas Figueiredo <lsf@cin.ufpe.br>, Thiago Menezes <tmc2@cin.ufpe.br>,
-   *           Thiago Domingues <tald@cin.ufpe.br>, Rafael Roberto <rar3@cin.ufpe.br>,
-   *           Thulio Araujo <tlsa@cin.ufpe.br>, Joao Victor <jvfl@cin.ufpe.br>,
-   *           Tomer Simis <tls@cin.ufpe.br>)
-   */
-  
-  /**
-   * Holds the maximum number of stages that will be used in the alignment algorithm.
-   * Each stage contains a different set of random forests and retrieves the binary
-   * code from a more "specialized" (i.e. smaller) region around the landmarks.
-   * @type {number}
-   * @static
-   */
-  tracking.LBF.maxNumStages = 4;
-
-  /**
-   * Holds the regressor that will be responsible for extracting the local features from 
-   * the image and guide the landmarks using the training data.
-   * @type {object}
-   * @protected
-   * @static
-   */
-  tracking.LBF.regressor_ = null; 
-  
-  /**
-   * Generates a set of landmarks for a set of faces
-   * @param {pixels} pixels The pixels in a linear [r,g,b,a,...] array.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {array} faces The list of faces detected in the image
-   * @return {array} The aligned landmarks, each set of landmarks corresponding
-   *     to a specific face.
-   * @static
-   */
-  tracking.LBF.align = function(pixels, width, height, faces){
-
-    if(tracking.LBF.regressor_ == null){
-      tracking.LBF.regressor_ = new tracking.LBF.Regressor(
-        tracking.LBF.maxNumStages
-      );
-    }
-// NOTE: is this thesholding suitable ? if it is on image, why no skin-color filter ? and a adaptative threshold
-    pixels = tracking.Image.grayscale(pixels, width, height, false);
-
-    pixels = tracking.Image.equalizeHist(pixels, width, height);
-
-    var shapes = new Array(faces.length);
-
-    for(var i in faces){
-
-      faces[i].height = faces[i].width;
-
-      var boundingBox = {};
-      boundingBox.startX = faces[i].x;
-      boundingBox.startY = faces[i].y;
-      boundingBox.width = faces[i].width;
-      boundingBox.height = faces[i].height;
-
-      shapes[i] = tracking.LBF.regressor_.predict(pixels, width, height, boundingBox);
-    }
-
-    return shapes;
-  }
-
-  /**
-   * Unprojects the landmarks shape from the bounding box.
-   * @param {matrix} shape The landmarks shape.
-   * @param {matrix} boudingBox The bounding box.
-   * @return {matrix} The landmarks shape projected into the bounding box.
-   * @static
-   * @protected
-   */
-  tracking.LBF.unprojectShapeToBoundingBox_ = function(shape, boundingBox){
-    var temp = new Array(shape.length);
-    for(var i=0; i < shape.length; i++){
-      temp[i] = [
-        (shape[i][0] - boundingBox.startX) / boundingBox.width,
-        (shape[i][1] - boundingBox.startY) / boundingBox.height
-      ];
-    }
-    return temp;
-  }
-
-  /**
-   * Projects the landmarks shape into the bounding box. The landmarks shape has
-   * normalized coordinates, so it is necessary to map these coordinates into
-   * the bounding box coordinates.
-   * @param {matrix} shape The landmarks shape.
-   * @param {matrix} boudingBox The bounding box.
-   * @return {matrix} The landmarks shape.
-   * @static
-   * @protected
-   */
-  tracking.LBF.projectShapeToBoundingBox_ = function(shape, boundingBox){
-    var temp = new Array(shape.length);
-    for(var i=0; i < shape.length; i++){
-      temp[i] = [
-        shape[i][0] * boundingBox.width + boundingBox.startX,
-        shape[i][1] * boundingBox.height + boundingBox.startY
-      ];
-    }
-    return temp;
-  }
-
-  /**
-   * Calculates the rotation and scale necessary to transform shape1 into shape2.
-   * @param {matrix} shape1 The shape to be transformed.
-   * @param {matrix} shape2 The shape to be transformed in.
-   * @return {[matrix, scalar]} The rotation matrix and scale that applied to shape1
-   *     results in shape2.
-   * @static
-   * @protected
-   */
-  tracking.LBF.similarityTransform_ = function(shape1, shape2){
-
-    var center1 = [0,0];
-    var center2 = [0,0];
-    for (var i = 0; i < shape1.length; i++) {
-      center1[0] += shape1[i][0];
-      center1[1] += shape1[i][1];
-      center2[0] += shape2[i][0];
-      center2[1] += shape2[i][1];
-    }
-    center1[0] /= shape1.length;
-    center1[1] /= shape1.length;
-    center2[0] /= shape2.length;
-    center2[1] /= shape2.length;
-
-    var temp1 = tracking.Matrix.clone(shape1);
-    var temp2 = tracking.Matrix.clone(shape2);
-    for(var i=0; i < shape1.length; i++){
-      temp1[i][0] -= center1[0];
-      temp1[i][1] -= center1[1];
-      temp2[i][0] -= center2[0];
-      temp2[i][1] -= center2[1];
-    }
-
-    var covariance1, covariance2;
-    var mean1, mean2;
-
-    var t = tracking.Matrix.calcCovarMatrix(temp1);
-    covariance1 = t[0];
-    mean1 = t[1];
-
-    t = tracking.Matrix.calcCovarMatrix(temp2);
-    covariance2 = t[0];
-    mean2 = t[1];
-
-    var s1 = Math.sqrt(tracking.Matrix.norm(covariance1));
-    var s2 = Math.sqrt(tracking.Matrix.norm(covariance2));
-
-    var scale = s1/s2;
-    temp1 = tracking.Matrix.mulScalar(1.0/s1, temp1);
-    temp2 = tracking.Matrix.mulScalar(1.0/s2, temp2);
-
-    var num = 0, den = 0;
-    for (var i = 0; i < shape1.length; i++) {
-      num = num + temp1[i][1] * temp2[i][0] - temp1[i][0] * temp2[i][1];
-      den = den + temp1[i][0] * temp2[i][0] + temp1[i][1] * temp2[i][1];
-    }
-
-    var norm = Math.sqrt(num*num + den*den);
-    var sin_theta = num/norm;
-    var cos_theta = den/norm;
-    var rotation = [
-      [cos_theta, -sin_theta],
-      [sin_theta, cos_theta]
-    ];
-
-    return [rotation, scale];
-  }
-
-  /**
-   * LBF Random Forest data structure.
-   * @static
-   * @constructor
-   */
-  tracking.LBF.RandomForest = function(forestIndex){
-    this.maxNumTrees = tracking.LBF.RegressorData[forestIndex].max_numtrees;
-    this.landmarkNum = tracking.LBF.RegressorData[forestIndex].num_landmark;
-    this.maxDepth = tracking.LBF.RegressorData[forestIndex].max_depth;
-    this.stages = tracking.LBF.RegressorData[forestIndex].stages; 
-
-    this.rfs = new Array(this.landmarkNum);
-    for(var i=0; i < this.landmarkNum; i++){
-      this.rfs[i] = new Array(this.maxNumTrees);
-      for(var j=0; j < this.maxNumTrees; j++){
-        this.rfs[i][j] = new tracking.LBF.Tree(forestIndex, i, j);
-      }
-    }
-  }
-
-  /**
-   * LBF Tree data structure.
-   * @static
-   * @constructor
-   */
-  tracking.LBF.Tree = function(forestIndex, landmarkIndex, treeIndex){
-    var data = tracking.LBF.RegressorData[forestIndex].landmarks[landmarkIndex][treeIndex];
-    this.maxDepth = data.max_depth;
-    this.maxNumNodes = data.max_numnodes;
-    this.nodes = data.nodes;
-    this.landmarkID = data.landmark_id;
-    this.numLeafnodes = data.num_leafnodes;
-    this.numNodes = data.num_nodes;
-    this.maxNumFeats = data.max_numfeats;
-    this.maxRadioRadius = data.max_radio_radius;
-    this.leafnodes = data.id_leafnodes;
-  }
-
-}());

common/tracking.js/src/alignment/Regressor.js

@@ -1,230 +0,0 @@
-(function() {
-
-  tracking.LBF = {};
-
-  /**
-   * LBF Regressor utility.
-   * @constructor
-   */
-  tracking.LBF.Regressor = function(maxNumStages){
-    this.maxNumStages = maxNumStages;
-
-    this.rfs = new Array(maxNumStages);
-    this.models = new Array(maxNumStages);
-    for(var i=0; i < maxNumStages; i++){
-      this.rfs[i] = new tracking.LBF.RandomForest(i);
-      this.models[i] = tracking.LBF.RegressorData[i].models;
-    }
-
-    this.meanShape = tracking.LBF.LandmarksData;
-  }
-
-  /**
-   * Predicts the position of the landmarks based on the bounding box of the face.
-   * @param {pixels} pixels The grayscale pixels in a linear array.
-   * @param {number} width Width of the image.
-   * @param {number} height Height of the image.
-   * @param {object} boudingBox Bounding box of the face to be aligned.
-   * @return {matrix} A matrix with each landmark position in a row [x,y].
-   */
-  tracking.LBF.Regressor.prototype.predict = function(pixels, width, height, boundingBox) {
-
-    var images = [];
-    var currentShapes = [];
-    var boundingBoxes = [];
-
-    var meanShapeClone = tracking.Matrix.clone(this.meanShape);
-
-    images.push({
-      'data': pixels,
-      'width': width,
-      'height': height
-    });
-    boundingBoxes.push(boundingBox);
-
-    currentShapes.push(tracking.LBF.projectShapeToBoundingBox_(meanShapeClone, boundingBox));
-
-    for(var stage = 0; stage < this.maxNumStages; stage++){
-      var binaryFeatures = tracking.LBF.Regressor.deriveBinaryFeat(this.rfs[stage], images, currentShapes, boundingBoxes, meanShapeClone);
-      this.applyGlobalPrediction(binaryFeatures, this.models[stage], currentShapes, boundingBoxes);
-    }
-
-    return currentShapes[0];
-  };
-
-  /**
-   * Multiplies the binary features of the landmarks with the regression matrix
-   * to obtain the displacement for each landmark. Then applies this displacement
-   * into the landmarks shape.
-   * @param {object} binaryFeatures The binary features for the landmarks.
-   * @param {object} models The regressor models.
-   * @param {matrix} currentShapes The landmarks shapes.
-   * @param {array} boudingBoxes The bounding boxes of the faces.
-   */
-  tracking.LBF.Regressor.prototype.applyGlobalPrediction = function(binaryFeatures, models, currentShapes, 
-    boundingBoxes){
-
-    var residual = currentShapes[0].length * 2;
-
-    var rotation = [];
-    var deltashape = new Array(residual/2);
-    for(var i=0; i < residual/2; i++){
-      deltashape[i] = [0.0, 0.0];
-    }
-
-    for(var i=0; i < currentShapes.length; i++){
-      for(var j=0; j < residual; j++){
-        var tmp = 0;
-        for(var lx=0, idx=0; (idx = binaryFeatures[i][lx].index) != -1; lx++){
-          if(idx <= models[j].nr_feature){
-            tmp += models[j].data[(idx - 1)] * binaryFeatures[i][lx].value;
-          }
-        }
-        if(j < residual/2){
-          deltashape[j][0] = tmp;
-        }else{
-          deltashape[j - residual/2][1] = tmp;
-        }
-      }
-
-      var res = tracking.LBF.similarityTransform_(tracking.LBF.unprojectShapeToBoundingBox_(currentShapes[i], boundingBoxes[i]), this.meanShape);
-      var rotation = tracking.Matrix.transpose(res[0]);
-
-      var s = tracking.LBF.unprojectShapeToBoundingBox_(currentShapes[i], boundingBoxes[i]);
-      s = tracking.Matrix.add(s, deltashape);
-
-      currentShapes[i] = tracking.LBF.projectShapeToBoundingBox_(s, boundingBoxes[i]);
-
-    }
-  };
-
-  /**
-   * Derives the binary features from the image for each landmark. 
-   * @param {object} forest The random forest to search for the best binary feature match.
-   * @param {array} images The images with pixels in a grayscale linear array.
-   * @param {array} currentShapes The current landmarks shape.
-   * @param {array} boudingBoxes The bounding boxes of the faces.
-   * @param {matrix} meanShape The mean shape of the current landmarks set.
-   * @return {array} The binary features extracted from the image and matched with the
-   *     training data.
-   * @static
-   */
-  tracking.LBF.Regressor.deriveBinaryFeat = function(forest, images, currentShapes, boundingBoxes, meanShape){
-
-    var binaryFeatures = new Array(images.length);
-    for(var i=0; i < images.length; i++){
-      var t = forest.maxNumTrees * forest.landmarkNum + 1;
-      binaryFeatures[i] = new Array(t);
-      for(var j=0; j < t; j++){
-        binaryFeatures[i][j] = {};
-      }
-    }
-
-    var leafnodesPerTree = 1 << (forest.maxDepth - 1);
-
-    for(var i=0; i < images.length; i++){
-
-      var projectedShape = tracking.LBF.unprojectShapeToBoundingBox_(currentShapes[i], boundingBoxes[i]);
-      var transform = tracking.LBF.similarityTransform_(projectedShape, meanShape);
-      
-      for(var j=0; j < forest.landmarkNum; j++){
-        for(var k=0; k < forest.maxNumTrees; k++){
-
-          var binaryCode = tracking.LBF.Regressor.getCodeFromTree(forest.rfs[j][k], images[i], 
-                              currentShapes[i], boundingBoxes[i], transform[0], transform[1]);
-
-          var index = j*forest.maxNumTrees + k;
-          binaryFeatures[i][index].index = leafnodesPerTree * index + binaryCode;
-          binaryFeatures[i][index].value = 1;
-
-        }
-      }
-      binaryFeatures[i][forest.landmarkNum * forest.maxNumTrees].index = -1;
-      binaryFeatures[i][forest.landmarkNum * forest.maxNumTrees].value = -1;
-    }
-    return binaryFeatures;
-
-  }
-
-  /**
-   * Gets the binary code for a specific tree in a random forest. For each landmark,
-   * the position from two pre-defined points are recovered from the training data
-   * and then the intensity of the pixels corresponding to these points is extracted 
-   * from the image and used to traverse the trees in the random forest. At the end,
-   * the ending nodes will be represented by 1, and the remaining nodes by 0.
-   * 
-   * +--------------------------- Random Forest -----------------------------+ 
-   * | Ø = Ending leaf                                                       |
-   * |                                                                       |
-   * |       O             O             O             O             O       |
-   * |     /   \         /   \         /   \         /   \         /   \     |
-   * |    O     O       O     O       O     O       O     O       O     O    |
-   * |   / \   / \     / \   / \     / \   / \     / \   / \     / \   / \   |
-   * |  Ø   O O   O   O   O Ø   O   O   Ø O   O   O   O Ø   O   O   O O   Ø  |
-   * |  1   0 0   0   0   0 1   0   0   1 0   0   0   0 1   0   0   0 0   1  |
-   * +-----------------------------------------------------------------------+
-   * Final binary code for this landmark: 10000010010000100001
-   *
-   * @param {object} forest The tree to be analyzed.
-   * @param {array} image The image with pixels in a grayscale linear array.
-   * @param {matrix} shape The current landmarks shape.
-   * @param {object} boudingBoxes The bounding box of the face.
-   * @param {matrix} rotation The rotation matrix used to transform the projected landmarks
-   *     into the mean shape.
-   * @param {number} scale The scale factor used to transform the projected landmarks
-   *     into the mean shape.
-   * @return {number} The binary code extracted from the tree.
-   * @static
-   */
-  tracking.LBF.Regressor.getCodeFromTree = function(tree, image, shape, boundingBox, rotation, scale){
-    var current = 0;
-    var bincode = 0;
-
-    while(true){
-      
-      var x1 = Math.cos(tree.nodes[current].feats[0]) * tree.nodes[current].feats[2] * tree.maxRadioRadius * boundingBox.width;
-      var y1 = Math.sin(tree.nodes[current].feats[0]) * tree.nodes[current].feats[2] * tree.maxRadioRadius * boundingBox.height;
-      var x2 = Math.cos(tree.nodes[current].feats[1]) * tree.nodes[current].feats[3] * tree.maxRadioRadius * boundingBox.width;
-      var y2 = Math.sin(tree.nodes[current].feats[1]) * tree.nodes[current].feats[3] * tree.maxRadioRadius * boundingBox.height;
-
-      var project_x1 = rotation[0][0] * x1 + rotation[0][1] * y1;
-      var project_y1 = rotation[1][0] * x1 + rotation[1][1] * y1;
-
-      var real_x1 = Math.floor(project_x1 + shape[tree.landmarkID][0]);
-      var real_y1 = Math.floor(project_y1 + shape[tree.landmarkID][1]);
-      real_x1 = Math.max(0.0, Math.min(real_x1, image.height - 1.0));
-      real_y1 = Math.max(0.0, Math.min(real_y1, image.width - 1.0));
-
-      var project_x2 = rotation[0][0] * x2 + rotation[0][1] * y2;
-      var project_y2 = rotation[1][0] * x2 + rotation[1][1] * y2;
-
-      var real_x2 = Math.floor(project_x2 + shape[tree.landmarkID][0]);
-      var real_y2 = Math.floor(project_y2 + shape[tree.landmarkID][1]);
-      real_x2 = Math.max(0.0, Math.min(real_x2, image.height - 1.0));
-      real_y2 = Math.max(0.0, Math.min(real_y2, image.width - 1.0));
-      var pdf = Math.floor(image.data[real_y1*image.width + real_x1]) - 
-          Math.floor(image.data[real_y2 * image.width +real_x2]);
-
-      if(pdf < tree.nodes[current].thresh){
-        current = tree.nodes[current].cnodes[0];
-      }else{
-        current = tree.nodes[current].cnodes[1];
-      }
-
-      if (tree.nodes[current].is_leafnode == 1) {
-        bincode = 1;
-        for (var i=0; i < tree.leafnodes.length; i++) {
-          if (tree.leafnodes[i] == current) {
-            return bincode;
-          }
-          bincode++;
-        }
-        return bincode;
-      }
-
-    }
-
-    return bincode;
-  }
-
-}());

common/tracking.js/src/detection/ViolaJones.js

@@ -1,280 +0,0 @@
-(function() {
-  /**
-   * ViolaJones utility.
-   * @static
-   * @constructor
-   */
-  tracking.ViolaJones = {};
-
-  /**
-   * Holds the minimum area of intersection that defines when a rectangle is
-   * from the same group. Often when a face is matched multiple rectangles are
-   * classified as possible rectangles to represent the face, when they
-   * intersects they are grouped as one face.
-   * @type {number}
-   * @default 0.5
-   * @static
-   */
-  tracking.ViolaJones.REGIONS_OVERLAP = 0.5;
-
-  /**
-   * Holds the HAAR cascade classifiers converted from OpenCV training.
-   * @type {array}
-   * @static
-   */
-  tracking.ViolaJones.classifiers = {};
-
-  /**
-   * Detects through the HAAR cascade data rectangles matches.
-   * @param {pixels} pixels The pixels in a linear [r,g,b,a,...] array.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {number} initialScale The initial scale to start the block
-   *     scaling.
-   * @param {number} scaleFactor The scale factor to scale the feature block.
-   * @param {number} stepSize The block step size.
-   * @param {number} edgesDensity Percentage density edges inside the
-   *     classifier block. Value from [0.0, 1.0], defaults to 0.2. If specified
-   *     edge detection will be applied to the image to prune dead areas of the
-   *     image, this can improve significantly performance.
-   * @param {number} data The HAAR cascade data.
-   * @return {array} Found rectangles.
-   * @static
-   */
-  tracking.ViolaJones.detect = function(pixels, width, height, initialScale, scaleFactor, stepSize, edgesDensity, data) {
-    var total = 0;
-    var rects = [];
-    var integralImage = new Int32Array(width * height);
-    var integralImageSquare = new Int32Array(width * height);
-    var tiltedIntegralImage = new Int32Array(width * height);
-
-    var integralImageSobel;
-    if (edgesDensity > 0) {
-      integralImageSobel = new Int32Array(width * height);
-    }
-
-    tracking.Image.computeIntegralImage(pixels, width, height, integralImage, integralImageSquare, tiltedIntegralImage, integralImageSobel);
-
-    var minWidth = data[0];
-    var minHeight = data[1];
-    var scale = initialScale * scaleFactor;
-    var blockWidth = (scale * minWidth) | 0;
-    var blockHeight = (scale * minHeight) | 0;
-
-    while (blockWidth < width && blockHeight < height) {
-      var step = (scale * stepSize + 0.5) | 0;
-      for (var i = 0; i < (height - blockHeight); i += step) {
-        for (var j = 0; j < (width - blockWidth); j += step) {
-
-          if (edgesDensity > 0) {
-            if (this.isTriviallyExcluded(edgesDensity, integralImageSobel, i, j, width, blockWidth, blockHeight)) {
-              continue;
-            }
-          }
-
-          if (this.evalStages_(data, integralImage, integralImageSquare, tiltedIntegralImage, i, j, width, blockWidth, blockHeight, scale)) {
-            rects[total++] = {
-              width: blockWidth,
-              height: blockHeight,
-              x: j,
-              y: i
-            };
-          }
-        }
-      }
-
-      scale *= scaleFactor;
-      blockWidth = (scale * minWidth) | 0;
-      blockHeight = (scale * minHeight) | 0;
-    }
-    return this.mergeRectangles_(rects);
-  };
-
-  /**
-   * Fast check to test whether the edges density inside the block is greater
-   * than a threshold, if true it tests the stages. This can improve
-   * significantly performance.
-   * @param {number} edgesDensity Percentage density edges inside the
-   *     classifier block.
-   * @param {array} integralImageSobel The integral image of a sobel image.
-   * @param {number} i Vertical position of the pixel to be evaluated.
-   * @param {number} j Horizontal position of the pixel to be evaluated.
-   * @param {number} width The image width.
-   * @return {boolean} True whether the block at position i,j can be skipped,
-   *     false otherwise.
-   * @static
-   * @protected
-   */
-  tracking.ViolaJones.isTriviallyExcluded = function(edgesDensity, integralImageSobel, i, j, width, blockWidth, blockHeight) {
-    var wbA = i * width + j;
-    var wbB = wbA + blockWidth;
-    var wbD = wbA + blockHeight * width;
-    var wbC = wbD + blockWidth;
-    var blockEdgesDensity = (integralImageSobel[wbA] - integralImageSobel[wbB] - integralImageSobel[wbD] + integralImageSobel[wbC]) / (blockWidth * blockHeight * 255);
-    if (blockEdgesDensity < edgesDensity) {
-      return true;
-    }
-    return false;
-  };
-
-  /**
-   * Evaluates if the block size on i,j position is a valid HAAR cascade
-   * stage.
-   * @param {number} data The HAAR cascade data.
-   * @param {number} i Vertical position of the pixel to be evaluated.
-   * @param {number} j Horizontal position of the pixel to be evaluated.
-   * @param {number} width The image width.
-   * @param {number} blockSize The block size.
-   * @param {number} scale The scale factor of the block size and its original
-   *     size.
-   * @param {number} inverseArea The inverse area of the block size.
-   * @return {boolean} Whether the region passes all the stage tests.
-   * @private
-   * @static
-   */
-  tracking.ViolaJones.evalStages_ = function(data, integralImage, integralImageSquare, tiltedIntegralImage, i, j, width, blockWidth, blockHeight, scale) {
-    var inverseArea = 1.0 / (blockWidth * blockHeight);
-    var wbA = i * width + j;
-    var wbB = wbA + blockWidth;
-    var wbD = wbA + blockHeight * width;
-    var wbC = wbD + blockWidth;
-    var mean = (integralImage[wbA] - integralImage[wbB] - integralImage[wbD] + integralImage[wbC]) * inverseArea;
-    var variance = (integralImageSquare[wbA] - integralImageSquare[wbB] - integralImageSquare[wbD] + integralImageSquare[wbC]) * inverseArea - mean * mean;
-
-    var standardDeviation = 1;
-    if (variance > 0) {
-      standardDeviation = Math.sqrt(variance);
-    }
-
-    var length = data.length;
-
-    for (var w = 2; w < length; ) {
-      var stageSum = 0;
-      var stageThreshold = data[w++];
-      var nodeLength = data[w++];
-
-      while (nodeLength--) {
-        var rectsSum = 0;
-        var tilted = data[w++];
-        var rectsLength = data[w++];
-
-        for (var r = 0; r < rectsLength; r++) {
-          var rectLeft = (j + data[w++] * scale + 0.5) | 0;
-          var rectTop = (i + data[w++] * scale + 0.5) | 0;
-          var rectWidth = (data[w++] * scale + 0.5) | 0;
-          var rectHeight = (data[w++] * scale + 0.5) | 0;
-          var rectWeight = data[w++];
-
-          var w1;
-          var w2;
-          var w3;
-          var w4;
-          if (tilted) {
-            // RectSum(r) = RSAT(x-h+w, y+w+h-1) + RSAT(x, y-1) - RSAT(x-h, y+h-1) - RSAT(x+w, y+w-1)
-            w1 = (rectLeft - rectHeight + rectWidth) + (rectTop + rectWidth + rectHeight - 1) * width;
-            w2 = rectLeft + (rectTop - 1) * width;
-            w3 = (rectLeft - rectHeight) + (rectTop + rectHeight - 1) * width;
-            w4 = (rectLeft + rectWidth) + (rectTop + rectWidth - 1) * width;
-            rectsSum += (tiltedIntegralImage[w1] + tiltedIntegralImage[w2] - tiltedIntegralImage[w3] - tiltedIntegralImage[w4]) * rectWeight;
-          } else {
-            // RectSum(r) = SAT(x-1, y-1) + SAT(x+w-1, y+h-1) - SAT(x-1, y+h-1) - SAT(x+w-1, y-1)
-            w1 = rectTop * width + rectLeft;
-            w2 = w1 + rectWidth;
-            w3 = w1 + rectHeight * width;
-            w4 = w3 + rectWidth;
-            rectsSum += (integralImage[w1] - integralImage[w2] - integralImage[w3] + integralImage[w4]) * rectWeight;
-            // TODO: Review the code below to analyze performance when using it instead.
-            // w1 = (rectLeft - 1) + (rectTop - 1) * width;
-            // w2 = (rectLeft + rectWidth - 1) + (rectTop + rectHeight - 1) * width;
-            // w3 = (rectLeft - 1) + (rectTop + rectHeight - 1) * width;
-            // w4 = (rectLeft + rectWidth - 1) + (rectTop - 1) * width;
-            // rectsSum += (integralImage[w1] + integralImage[w2] - integralImage[w3] - integralImage[w4]) * rectWeight;
-          }
-        }
-
-        var nodeThreshold = data[w++];
-        var nodeLeft = data[w++];
-        var nodeRight = data[w++];
-
-        if (rectsSum * inverseArea < nodeThreshold * standardDeviation) {
-          stageSum += nodeLeft;
-        } else {
-          stageSum += nodeRight;
-        }
-      }
-
-      if (stageSum < stageThreshold) {
-        return false;
-      }
-    }
-    return true;
-  };
-
-  /**
-   * Postprocess the detected sub-windows in order to combine overlapping
-   * detections into a single detection.
-   * @param {array} rects
-   * @return {array}
-   * @private
-   * @static
-   */
-  tracking.ViolaJones.mergeRectangles_ = function(rects) {
-    var disjointSet = new tracking.DisjointSet(rects.length);
-
-    for (var i = 0; i < rects.length; i++) {
-      var r1 = rects[i];
-      for (var j = 0; j < rects.length; j++) {
-        var r2 = rects[j];
-        if (tracking.Math.intersectRect(r1.x, r1.y, r1.x + r1.width, r1.y + r1.height, r2.x, r2.y, r2.x + r2.width, r2.y + r2.height)) {
-          var x1 = Math.max(r1.x, r2.x);
-          var y1 = Math.max(r1.y, r2.y);
-          var x2 = Math.min(r1.x + r1.width, r2.x + r2.width);
-          var y2 = Math.min(r1.y + r1.height, r2.y + r2.height);
-          var overlap = (x1 - x2) * (y1 - y2);
-          var area1 = (r1.width * r1.height);
-          var area2 = (r2.width * r2.height);
-
-          if ((overlap / (area1 * (area1 / area2)) >= this.REGIONS_OVERLAP) &&
-            (overlap / (area2 * (area1 / area2)) >= this.REGIONS_OVERLAP)) {
-            disjointSet.union(i, j);
-          }
-        }
-      }
-    }
-
-    var map = {};
-    for (var k = 0; k < disjointSet.length; k++) {
-      var rep = disjointSet.find(k);
-      if (!map[rep]) {
-        map[rep] = {
-          total: 1,
-          width: rects[k].width,
-          height: rects[k].height,
-          x: rects[k].x,
-          y: rects[k].y
-        };
-        continue;
-      }
-      map[rep].total++;
-      map[rep].width += rects[k].width;
-      map[rep].height += rects[k].height;
-      map[rep].x += rects[k].x;
-      map[rep].y += rects[k].y;
-    }
-
-    var result = [];
-    Object.keys(map).forEach(function(key) {
-      var rect = map[key];
-      result.push({
-        total: rect.total,
-        width: (rect.width / rect.total + 0.5) | 0,
-        height: (rect.height / rect.total + 0.5) | 0,
-        x: (rect.x / rect.total + 0.5) | 0,
-        y: (rect.y / rect.total + 0.5) | 0
-      });
-    });
-
-    return result;
-  };
-
-}());

common/tracking.js/src/features/Brief.js

@@ -1,198 +0,0 @@
-(function() {
-  /**
-   * Brief intends for "Binary Robust Independent Elementary Features".This
-   * method generates a binary string for each keypoint found by an extractor
-   * method.
-   * @static
-   * @constructor
-   */
-  tracking.Brief = {};
-
-  /**
-   * The set of binary tests is defined by the nd (x,y)-location pairs
-   * uniquely chosen during the initialization. Values could vary between N =
-   * 128,256,512. N=128 yield good compromises between speed, storage
-   * efficiency, and recognition rate.
-   * @type {number}
-   */
-  tracking.Brief.N = 512;
-
-  /**
-   * Caches coordinates values of (x,y)-location pairs uniquely chosen during
-   * the initialization.
-   * @type {Object.<number, Int32Array>}
-   * @private
-   * @static
-   */
-  tracking.Brief.randomImageOffsets_ = {};
-
-  /**
-   * Caches delta values of (x,y)-location pairs uniquely chosen during
-   * the initialization.
-   * @type {Int32Array}
-   * @private
-   * @static
-   */
-  tracking.Brief.randomWindowOffsets_ = null;
-
-  /**
-   * Generates a binary string for each found keypoints extracted using an
-   * extractor method.
-   * @param {array} The grayscale pixels in a linear [p1,p2,...] array.
-   * @param {number} width The image width.
-   * @param {array} keypoints
-   * @return {Int32Array} Returns an array where for each four sequence int
-   *     values represent the descriptor binary string (128 bits) necessary
-   *     to describe the corner, e.g. [0,0,0,0, 0,0,0,0, ...].
-   * @static
-   */
-  tracking.Brief.getDescriptors = function(pixels, width, keypoints) {
-    // Optimizing divide by 32 operation using binary shift
-    // (this.N >> 5) === this.N/32.
-    var descriptors = new Int32Array((keypoints.length >> 1) * (this.N >> 5));
-    var descriptorWord = 0;
-    var offsets = this.getRandomOffsets_(width);
-    var position = 0;
-
-    for (var i = 0; i < keypoints.length; i += 2) {
-      var w = width * keypoints[i + 1] + keypoints[i];
-
-      var offsetsPosition = 0;
-      for (var j = 0, n = this.N; j < n; j++) {
-        if (pixels[offsets[offsetsPosition++] + w] < pixels[offsets[offsetsPosition++] + w]) {
-          // The bit in the position `j % 32` of descriptorWord should be set to 1. We do
-          // this by making an OR operation with a binary number that only has the bit
-          // in that position set to 1. That binary number is obtained by shifting 1 left by
-          // `j % 32` (which is the same as `j & 31` left) positions.
-          descriptorWord |= 1 << (j & 31);
-        }
-
-        // If the next j is a multiple of 32, we will need to use a new descriptor word to hold
-        // the next results.
-        if (!((j + 1) & 31)) {
-          descriptors[position++] = descriptorWord;
-          descriptorWord = 0;
-        }
-      }
-    }
-
-    return descriptors;
-  };
-
-  /**
-   * Matches sets of features {mi} and {m′j} extracted from two images taken
-   * from similar, and often successive, viewpoints. A classical procedure
-   * runs as follows. For each point {mi} in the first image, search in a
-   * region of the second image around location {mi} for point {m′j}. The
-   * search is based on the similarity of the local image windows, also known
-   * as kernel windows, centered on the points, which strongly characterizes
-   * the points when the images are sufficiently close. Once each keypoint is
-   * described with its binary string, they need to be compared with the
-   * closest matching point. Distance metric is critical to the performance of
-   * in- trusion detection systems. Thus using binary strings reduces the size
-   * of the descriptor and provides an interesting data structure that is fast
-   * to operate whose similarity can be measured by the Hamming distance.
-   * @param {array} keypoints1
-   * @param {array} descriptors1
-   * @param {array} keypoints2
-   * @param {array} descriptors2
-   * @return {Int32Array} Returns an array where the index is the corner1
-   *     index coordinate, and the value is the corresponding match index of
-   *     corner2, e.g. keypoints1=[x0,y0,x1,y1,...] and
-   *     keypoints2=[x'0,y'0,x'1,y'1,...], if x0 matches x'1 and x1 matches x'0,
-   *     the return array would be [3,0].
-   * @static
-   */
-  tracking.Brief.match = function(keypoints1, descriptors1, keypoints2, descriptors2) {
-    var len1 = keypoints1.length >> 1;
-    var len2 = keypoints2.length >> 1;
-    var matches = new Array(len1);
-
-    for (var i = 0; i < len1; i++) {
-      var min = Infinity;
-      var minj = 0;
-      for (var j = 0; j < len2; j++) {
-        var dist = 0;
-        // Optimizing divide by 32 operation using binary shift
-        // (this.N >> 5) === this.N/32.
-        for (var k = 0, n = this.N >> 5; k < n; k++) {
-          dist += tracking.Math.hammingWeight(descriptors1[i * n + k] ^ descriptors2[j * n + k]);
-        }
-        if (dist < min) {
-          min = dist;
-          minj = j;
-        }
-      }
-      matches[i] = {
-        index1: i,
-        index2: minj,
-        keypoint1: [keypoints1[2 * i], keypoints1[2 * i + 1]],
-        keypoint2: [keypoints2[2 * minj], keypoints2[2 * minj + 1]],
-        confidence: 1 - min / this.N
-      };
-    }
-
-    return matches;
-  };
-
-  /**
-   * Removes matches outliers by testing matches on both directions.
-   * @param {array} keypoints1
-   * @param {array} descriptors1
-   * @param {array} keypoints2
-   * @param {array} descriptors2
-   * @return {Int32Array} Returns an array where the index is the corner1
-   *     index coordinate, and the value is the corresponding match index of
-   *     corner2, e.g. keypoints1=[x0,y0,x1,y1,...] and
-   *     keypoints2=[x'0,y'0,x'1,y'1,...], if x0 matches x'1 and x1 matches x'0,
-   *     the return array would be [3,0].
-   * @static
-   */
-  tracking.Brief.reciprocalMatch = function(keypoints1, descriptors1, keypoints2, descriptors2) {
-    var matches = [];
-    if (keypoints1.length === 0 || keypoints2.length === 0) {
-      return matches;
-    }
-
-    var matches1 = tracking.Brief.match(keypoints1, descriptors1, keypoints2, descriptors2);
-    var matches2 = tracking.Brief.match(keypoints2, descriptors2, keypoints1, descriptors1);
-    for (var i = 0; i < matches1.length; i++) {
-      if (matches2[matches1[i].index2].index2 === i) {
-        matches.push(matches1[i]);
-      }
-    }
-    return matches;
-  };
-
-  /**
-   * Gets the coordinates values of (x,y)-location pairs uniquely chosen
-   * during the initialization.
-   * @return {array} Array with the random offset values.
-   * @private
-   */
-  tracking.Brief.getRandomOffsets_ = function(width) {
-    if (!this.randomWindowOffsets_) {
-      var windowPosition = 0;
-      var windowOffsets = new Int32Array(4 * this.N);
-      for (var i = 0; i < this.N; i++) {
-        windowOffsets[windowPosition++] = Math.round(tracking.Math.uniformRandom(-15, 16));
-        windowOffsets[windowPosition++] = Math.round(tracking.Math.uniformRandom(-15, 16));
-        windowOffsets[windowPosition++] = Math.round(tracking.Math.uniformRandom(-15, 16));
-        windowOffsets[windowPosition++] = Math.round(tracking.Math.uniformRandom(-15, 16));
-      }
-      this.randomWindowOffsets_ = windowOffsets;
-    }
-
-    if (!this.randomImageOffsets_[width]) {
-      var imagePosition = 0;
-      var imageOffsets = new Int32Array(2 * this.N);
-      for (var j = 0; j < this.N; j++) {
-        imageOffsets[imagePosition++] = this.randomWindowOffsets_[4 * j] * width + this.randomWindowOffsets_[4 * j + 1];
-        imageOffsets[imagePosition++] = this.randomWindowOffsets_[4 * j + 2] * width + this.randomWindowOffsets_[4 * j + 3];
-      }
-      this.randomImageOffsets_[width] = imageOffsets;
-    }
-
-    return this.randomImageOffsets_[width];
-  };
-}());

common/tracking.js/src/features/Fast.js

@@ -1,250 +0,0 @@
-(function() {
-  /**
-   * FAST intends for "Features from Accelerated Segment Test". This method
-   * performs a point segment test corner detection. The segment test
-   * criterion operates by considering a circle of sixteen pixels around the
-   * corner candidate p. The detector classifies p as a corner if there exists
-   * a set of n contiguous pixelsin the circle which are all brighter than the
-   * intensity of the candidate pixel Ip plus a threshold t, or all darker
-   * than Ip − t.
-   *
-   *       15 00 01
-   *    14          02
-   * 13                03
-   * 12       []       04
-   * 11                05
-   *    10          06
-   *       09 08 07
-   *
-   * For more reference:
-   * http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.60.3991&rep=rep1&type=pdf
-   * @static
-   * @constructor
-   */
-  tracking.Fast = {};
-
-  /**
-   * Holds the threshold to determine whether the tested pixel is brighter or
-   * darker than the corner candidate p.
-   * @type {number}
-   * @default 40
-   * @static
-   */
-  tracking.Fast.THRESHOLD = 40;
-
-  /**
-   * Caches coordinates values of the circle surrounding the pixel candidate p.
-   * @type {Object.<number, Int32Array>}
-   * @private
-   * @static
-   */
-  tracking.Fast.circles_ = {};
-
-  /**
-   * Finds corners coordinates on the graysacaled image.
-   * @param {array} The grayscale pixels in a linear [p1,p2,...] array.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {number} threshold to determine whether the tested pixel is brighter or
-   *     darker than the corner candidate p. Default value is 40.
-   * @return {array} Array containing the coordinates of all found corners,
-   *     e.g. [x0,y0,x1,y1,...], where P(x0,y0) represents a corner coordinate.
-   * @static
-   */
-  tracking.Fast.findCorners = function(pixels, width, height, opt_threshold) {
-    var circleOffsets = this.getCircleOffsets_(width);
-    var circlePixels = new Int32Array(16);
-    var corners = [];
-
-    if (opt_threshold === undefined) {
-      opt_threshold = this.THRESHOLD;
-    }
-
-    // When looping through the image pixels, skips the first three lines from
-    // the image boundaries to constrain the surrounding circle inside the image
-    // area.
-    for (var i = 3; i < height - 3; i++) {
-      for (var j = 3; j < width - 3; j++) {
-        var w = i * width + j;
-        var p = pixels[w];
-
-        // Loops the circle offsets to read the pixel value for the sixteen
-        // surrounding pixels.
-        for (var k = 0; k < 16; k++) {
-          circlePixels[k] = pixels[w + circleOffsets[k]];
-        }
-
-        if (this.isCorner(p, circlePixels, opt_threshold)) {
-          // The pixel p is classified as a corner, as optimization increment j
-          // by the circle radius 3 to skip the neighbor pixels inside the
-          // surrounding circle. This can be removed without compromising the
-          // result.
-          corners.push(j, i);
-          j += 3;
-        }
-      }
-    }
-
-    return corners;
-  };
-
-  /**
-   * Checks if the circle pixel is brighter than the candidate pixel p by
-   * a threshold.
-   * @param {number} circlePixel The circle pixel value.
-   * @param {number} p The value of the candidate pixel p.
-   * @param {number} threshold
-   * @return {Boolean}
-   * @static
-   */
-  tracking.Fast.isBrighter = function(circlePixel, p, threshold) {
-    return circlePixel - p > threshold;
-  };
-
-  /**
-   * Checks if the circle pixel is within the corner of the candidate pixel p
-   * by a threshold.
-   * @param {number} p The value of the candidate pixel p.
-   * @param {number} circlePixel The circle pixel value.
-   * @param {number} threshold
-   * @return {Boolean}
-   * @static
-   */
-  tracking.Fast.isCorner = function(p, circlePixels, threshold) {
-    if (this.isTriviallyExcluded(circlePixels, p, threshold)) {
-      return false;
-    }
-
-    for (var x = 0; x < 16; x++) {
-      var darker = true;
-      var brighter = true;
-
-      for (var y = 0; y < 9; y++) {
-        var circlePixel = circlePixels[(x + y) & 15];
-
-        if (!this.isBrighter(p, circlePixel, threshold)) {
-          brighter = false;
-          if (darker === false) {
-            break;
-          }
-        }
-
-        if (!this.isDarker(p, circlePixel, threshold)) {
-          darker = false;
-          if (brighter === false) {
-            break;
-          }
-        }
-      }
-
-      if (brighter || darker) {
-        return true;
-      }
-    }
-
-    return false;
-  };
-
-  /**
-   * Checks if the circle pixel is darker than the candidate pixel p by
-   * a threshold.
-   * @param {number} circlePixel The circle pixel value.
-   * @param {number} p The value of the candidate pixel p.
-   * @param {number} threshold
-   * @return {Boolean}
-   * @static
-   */
-  tracking.Fast.isDarker = function(circlePixel, p, threshold) {
-    return p - circlePixel > threshold;
-  };
-
-  /**
-   * Fast check to test if the candidate pixel is a trivially excluded value.
-   * In order to be a corner, the candidate pixel value should be darker or
-   * brighter than 9-12 surrounding pixels, when at least three of the top,
-   * bottom, left and right pixels are brighter or darker it can be
-   * automatically excluded improving the performance.
-   * @param {number} circlePixel The circle pixel value.
-   * @param {number} p The value of the candidate pixel p.
-   * @param {number} threshold
-   * @return {Boolean}
-   * @static
-   * @protected
-   */
-  tracking.Fast.isTriviallyExcluded = function(circlePixels, p, threshold) {
-    var count = 0;
-    var circleBottom = circlePixels[8];
-    var circleLeft = circlePixels[12];
-    var circleRight = circlePixels[4];
-    var circleTop = circlePixels[0];
-
-    if (this.isBrighter(circleTop, p, threshold)) {
-      count++;
-    }
-    if (this.isBrighter(circleRight, p, threshold)) {
-      count++;
-    }
-    if (this.isBrighter(circleBottom, p, threshold)) {
-      count++;
-    }
-    if (this.isBrighter(circleLeft, p, threshold)) {
-      count++;
-    }
-
-    if (count < 3) {
-      count = 0;
-      if (this.isDarker(circleTop, p, threshold)) {
-        count++;
-      }
-      if (this.isDarker(circleRight, p, threshold)) {
-        count++;
-      }
-      if (this.isDarker(circleBottom, p, threshold)) {
-        count++;
-      }
-      if (this.isDarker(circleLeft, p, threshold)) {
-        count++;
-      }
-      if (count < 3) {
-        return true;
-      }
-    }
-
-    return false;
-  };
-
-  /**
-   * Gets the sixteen offset values of the circle surrounding pixel.
-   * @param {number} width The image width.
-   * @return {array} Array with the sixteen offset values of the circle
-   *     surrounding pixel.
-   * @private
-   */
-  tracking.Fast.getCircleOffsets_ = function(width) {
-    if (this.circles_[width]) {
-      return this.circles_[width];
-    }
-
-    var circle = new Int32Array(16);
-
-    circle[0] = -width - width - width;
-    circle[1] = circle[0] + 1;
-    circle[2] = circle[1] + width + 1;
-    circle[3] = circle[2] + width + 1;
-    circle[4] = circle[3] + width;
-    circle[5] = circle[4] + width;
-    circle[6] = circle[5] + width - 1;
-    circle[7] = circle[6] + width - 1;
-    circle[8] = circle[7] - 1;
-    circle[9] = circle[8] - 1;
-    circle[10] = circle[9] - width - 1;
-    circle[11] = circle[10] - width - 1;
-    circle[12] = circle[11] - width;
-    circle[13] = circle[12] - width;
-    circle[14] = circle[13] - width + 1;
-    circle[15] = circle[14] - width + 1;
-
-    this.circles_[width] = circle;
-    return circle;
-  };
-}());

common/tracking.js/src/math/Math.js

@@ -1,82 +0,0 @@
-(function() {
-  /**
-   * Math utility.
-   * @static
-   * @constructor
-   */
-  tracking.Math = {};
-
-  /**
-   * Euclidean distance between two points P(x0, y0) and P(x1, y1).
-   * @param {number} x0 Horizontal coordinate of P0.
-   * @param {number} y0 Vertical coordinate of P0.
-   * @param {number} x1 Horizontal coordinate of P1.
-   * @param {number} y1 Vertical coordinate of P1.
-   * @return {number} The euclidean distance.
-   */
-  tracking.Math.distance = function(x0, y0, x1, y1) {
-    var dx = x1 - x0;
-    var dy = y1 - y0;
-
-    return Math.sqrt(dx * dx + dy * dy);
-  };
-
-  /**
-   * Calculates the Hamming weight of a string, which is the number of symbols that are
-   * different from the zero-symbol of the alphabet used. It is thus
-   * equivalent to the Hamming distance from the all-zero string of the same
-   * length. For the most typical case, a string of bits, this is the number
-   * of 1's in the string.
-   *
-   * Example:
-   *
-   * <pre>
-   *  Binary string     Hamming weight
-   *   11101                 4
-   *   11101010              5
-   * </pre>
-   *
-   * @param {number} i Number that holds the binary string to extract the hamming weight.
-   * @return {number} The hamming weight.
-   */
-  tracking.Math.hammingWeight = function(i) {
-    i = i - ((i >> 1) & 0x55555555);
-    i = (i & 0x33333333) + ((i >> 2) & 0x33333333);
-
-    return ((i + (i >> 4) & 0xF0F0F0F) * 0x1010101) >> 24;
-  };
-
-  /**
-   * Generates a random number between [a, b] interval.
-   * @param {number} a
-   * @param {number} b
-   * @return {number}
-   */
-  tracking.Math.uniformRandom = function(a, b) {
-    return a + Math.random() * (b - a);
-  };
-
-  /**
-   * Tests if a rectangle intersects with another.
-   *
-   *  <pre>
-   *  x0y0 --------       x2y2 --------
-   *      |       |           |       |
-   *      -------- x1y1       -------- x3y3
-   * </pre>
-   *
-   * @param {number} x0 Horizontal coordinate of P0.
-   * @param {number} y0 Vertical coordinate of P0.
-   * @param {number} x1 Horizontal coordinate of P1.
-   * @param {number} y1 Vertical coordinate of P1.
-   * @param {number} x2 Horizontal coordinate of P2.
-   * @param {number} y2 Vertical coordinate of P2.
-   * @param {number} x3 Horizontal coordinate of P3.
-   * @param {number} y3 Vertical coordinate of P3.
-   * @return {boolean}
-   */
-  tracking.Math.intersectRect = function(x0, y0, x1, y1, x2, y2, x3, y3) {
-    return !(x2 > x1 || x3 < x0 || y2 > y1 || y3 < y0);
-  };
-
-}());

common/tracking.js/src/math/Matrix.js

@@ -1,185 +0,0 @@
-(function() {
-  /**
-   * Matrix utility.
-   * @static
-   * @constructor
-   */
-  tracking.Matrix = {};
-
-  /**
-   * Loops the array organized as major-row order and executes `fn` callback
-   * for each iteration. The `fn` callback receives the following parameters:
-   * `(r,g,b,a,index,i,j)`, where `r,g,b,a` represents the pixel color with
-   * alpha channel, `index` represents the position in the major-row order
-   * array and `i,j` the respective indexes positions in two dimensions.
-   * @param {array} pixels The pixels in a linear [r,g,b,a,...] array to loop
-   *     through.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {function} fn The callback function for each pixel.
-   * @param {number} opt_jump Optional jump for the iteration, by default it
-   *     is 1, hence loops all the pixels of the array.
-   * @static
-   */
-  tracking.Matrix.forEach = function(pixels, width, height, fn, opt_jump) {
-    opt_jump = opt_jump || 1;
-    for (var i = 0; i < height; i += opt_jump) {
-      for (var j = 0; j < width; j += opt_jump) {
-        var w = i * width * 4 + j * 4;
-        fn.call(this, pixels[w], pixels[w + 1], pixels[w + 2], pixels[w + 3], w, i, j);
-      }
-    }
-  };
-
-  /**
-   * Calculates the per-element subtraction of two NxM matrices and returns a 
-   * new NxM matrix as the result.
-   * @param {matrix} a The first matrix.
-   * @param {matrix} a The second matrix.
-   * @static
-   */
-  tracking.Matrix.sub = function(a, b){
-    var res = tracking.Matrix.clone(a);
-    for(var i=0; i < res.length; i++){
-      for(var j=0; j < res[i].length; j++){
-        res[i][j] -= b[i][j]; 
-      }
-    }
-    return res;
-  }
-
-  /**
-   * Calculates the per-element sum of two NxM matrices and returns a new NxM
-   * NxM matrix as the result.
-   * @param {matrix} a The first matrix.
-   * @param {matrix} a The second matrix.
-   * @static
-   */
-  tracking.Matrix.add = function(a, b){
-    var res = tracking.Matrix.clone(a);
-    for(var i=0; i < res.length; i++){
-      for(var j=0; j < res[i].length; j++){
-        res[i][j] += b[i][j]; 
-      }
-    }
-    return res;
-  }
-
-  /**
-   * Clones a matrix (or part of it) and returns a new matrix as the result.
-   * @param {matrix} src The matrix to be cloned.
-   * @param {number} width The second matrix.
-   * @static
-   */
-  tracking.Matrix.clone = function(src, width, height){
-    width = width || src[0].length;
-    height = height || src.length;
-    var temp = new Array(height);
-    var i = height;
-    while(i--){
-      temp[i] = new Array(width);
-      var j = width;
-      while(j--) temp[i][j] = src[i][j];
-    } 
-    return temp;
-  }
-
-  /**
-   * Multiply a matrix by a scalar and returns a new matrix as the result.
-   * @param {number} scalar The scalar to multiply the matrix by.
-   * @param {matrix} src The matrix to be multiplied.
-   * @static
-   */
-  tracking.Matrix.mulScalar = function(scalar, src){
-    var res = tracking.Matrix.clone(src);
-    for(var i=0; i < src.length; i++){
-      for(var j=0; j < src[i].length; j++){
-        res[i][j] *= scalar;
-      }
-    }
-    return res;
-  }
-
-  /**
-   * Transpose a matrix and returns a new matrix as the result.
-   * @param {matrix} src The matrix to be transposed.
-   * @static
-   */
-  tracking.Matrix.transpose = function(src){
-    var transpose = new Array(src[0].length);
-    for(var i=0; i < src[0].length; i++){
-      transpose[i] = new Array(src.length);
-      for(var j=0; j < src.length; j++){
-        transpose[i][j] = src[j][i];
-      }
-    }
-    return transpose;
-  }
-
-  /**
-   * Multiply an MxN matrix with an NxP matrix and returns a new MxP matrix
-   * as the result.
-   * @param {matrix} a The first matrix.
-   * @param {matrix} b The second matrix.
-   * @static
-   */
-  tracking.Matrix.mul = function(a, b) {
-    var res = new Array(a.length);
-    for (var i = 0; i < a.length; i++) {
-      res[i] = new Array(b[0].length);
-      for (var j = 0; j < b[0].length; j++) {
-        res[i][j] = 0;            
-        for (var k = 0; k < a[0].length; k++) {
-          res[i][j] += a[i][k] * b[k][j];
-        }
-      }
-    }
-    return res;
-  }
-
-  /**
-   * Calculates the absolute norm of a matrix.
-   * @param {matrix} src The matrix which norm will be calculated.
-   * @static
-   */
-  tracking.Matrix.norm = function(src){
-    var res = 0;
-    for(var i=0; i < src.length; i++){
-      for(var j=0; j < src[i].length; j++){
-        res += src[i][j]*src[i][j];
-      }
-    }
-    return Math.sqrt(res);
-  }
-
-  /**
-   * Calculates and returns the covariance matrix of a set of vectors as well
-   * as the mean of the matrix.
-   * @param {matrix} src The matrix which covariance matrix will be calculated.
-   * @static
-   */
-  tracking.Matrix.calcCovarMatrix = function(src){
-
-    var mean = new Array(src.length);
-    for(var i=0; i < src.length; i++){
-      mean[i] = [0.0];
-      for(var j=0; j < src[i].length; j++){
-        mean[i][0] += src[i][j]/src[i].length;
-      }
-    }
-
-    var deltaFull = tracking.Matrix.clone(mean);
-    for(var i=0; i < deltaFull.length; i++){
-      for(var j=0; j < src[0].length - 1; j++){
-        deltaFull[i].push(deltaFull[i][0]);
-      }
-    }
-
-    var a = tracking.Matrix.sub(src, deltaFull);
-    var b = tracking.Matrix.transpose(a);
-    var covar = tracking.Matrix.mul(b,a); 
-    return [covar, mean];
-
-  }
-
-}());

common/tracking.js/src/pose/EPnP.js

@@ -1,10 +0,0 @@
-(function() {
-  /**
-   * EPnp utility.
-   * @static
-   * @constructor
-   */
-  tracking.EPnP = {};
-
-  tracking.EPnP.solve = function(objectPoints, imagePoints, cameraMatrix) {};
-}());

common/tracking.js/src/trackers/ColorTracker.js

@@ -1,425 +0,0 @@
-(function() {
-  /**
-   * ColorTracker utility to track colored blobs in a frame using color
-   * difference evaluation.
-   * @constructor
-   * @param {string|Array.<string>} opt_colors Optional colors to track.
-   * @extends {tracking.Tracker}
-   */
-  tracking.ColorTracker = function(opt_colors) {
-    tracking.ColorTracker.base(this, 'constructor');
-
-    if (typeof opt_colors === 'string') {
-      opt_colors = [opt_colors];
-    }
-
-    if (opt_colors) {
-      opt_colors.forEach(function(color) {
-        if (!tracking.ColorTracker.getColor(color)) {
-          throw new Error('Color not valid, try `new tracking.ColorTracker("magenta")`.');
-        }
-      });
-      this.setColors(opt_colors);
-    }
-  };
-
-  tracking.inherits(tracking.ColorTracker, tracking.Tracker);
-
-  /**
-   * Holds the known colors.
-   * @type {Object.<string, function>}
-   * @private
-   * @static
-   */
-  tracking.ColorTracker.knownColors_ = {};
-
-  /**
-   * Caches coordinates values of the neighbours surrounding a pixel.
-   * @type {Object.<number, Int32Array>}
-   * @private
-   * @static
-   */
-  tracking.ColorTracker.neighbours_ = {};
-
-  /**
-   * Registers a color as known color.
-   * @param {string} name The color name.
-   * @param {function} fn The color function to test if the passed (r,g,b) is
-   *     the desired color.
-   * @static
-   */
-  tracking.ColorTracker.registerColor = function(name, fn) {
-    tracking.ColorTracker.knownColors_[name] = fn;
-  };
-
-  /**
-   * Gets the known color function that is able to test whether an (r,g,b) is
-   * the desired color.
-   * @param {string} name The color name.
-   * @return {function} The known color test function.
-   * @static
-   */
-  tracking.ColorTracker.getColor = function(name) {
-    return tracking.ColorTracker.knownColors_[name];
-  };
-
-  /**
-   * Holds the colors to be tracked by the `ColorTracker` instance.
-   * @default ['magenta']
-   * @type {Array.<string>}
-   */
-  tracking.ColorTracker.prototype.colors = ['magenta'];
-
-  /**
-   * Holds the minimum dimension to classify a rectangle.
-   * @default 20
-   * @type {number}
-   */
-  tracking.ColorTracker.prototype.minDimension = 20;
-
-  /**
-   * Holds the maximum dimension to classify a rectangle.
-   * @default Infinity
-   * @type {number}
-   */
-  tracking.ColorTracker.prototype.maxDimension = Infinity;
-
-
-  /**
-   * Holds the minimum group size to be classified as a rectangle.
-   * @default 30
-   * @type {number}
-   */
-  tracking.ColorTracker.prototype.minGroupSize = 30;
-
-  /**
-   * Calculates the central coordinate from the cloud points. The cloud points
-   * are all points that matches the desired color.
-   * @param {Array.<number>} cloud Major row order array containing all the
-   *     points from the desired color, e.g. [x1, y1, c2, y2, ...].
-   * @param {number} total Total numbers of pixels of the desired color.
-   * @return {object} Object containing the x, y and estimated z coordinate of
-   *     the blog extracted from the cloud points.
-   * @private
-   */
-  tracking.ColorTracker.prototype.calculateDimensions_ = function(cloud, total) {
-    var maxx = -1;
-    var maxy = -1;
-    var minx = Infinity;
-    var miny = Infinity;
-
-    for (var c = 0; c < total; c += 2) {
-      var x = cloud[c];
-      var y = cloud[c + 1];
-
-      if (x < minx) {
-        minx = x;
-      }
-      if (x > maxx) {
-        maxx = x;
-      }
-      if (y < miny) {
-        miny = y;
-      }
-      if (y > maxy) {
-        maxy = y;
-      }
-    }
-
-    return {
-      width: maxx - minx,
-      height: maxy - miny,
-      x: minx,
-      y: miny
-    };
-  };
-
-  /**
-   * Gets the colors being tracked by the `ColorTracker` instance.
-   * @return {Array.<string>}
-   */
-  tracking.ColorTracker.prototype.getColors = function() {
-    return this.colors;
-  };
-
-  /**
-   * Gets the minimum dimension to classify a rectangle.
-   * @return {number}
-   */
-  tracking.ColorTracker.prototype.getMinDimension = function() {
-    return this.minDimension;
-  };
-
-  /**
-   * Gets the maximum dimension to classify a rectangle.
-   * @return {number}
-   */
-  tracking.ColorTracker.prototype.getMaxDimension = function() {
-    return this.maxDimension;
-  };
-
-  /**
-   * Gets the minimum group size to be classified as a rectangle.
-   * @return {number}
-   */
-  tracking.ColorTracker.prototype.getMinGroupSize = function() {
-    return this.minGroupSize;
-  };
-
-  /**
-   * Gets the eight offset values of the neighbours surrounding a pixel.
-   * @param {number} width The image width.
-   * @return {array} Array with the eight offset values of the neighbours
-   *     surrounding a pixel.
-   * @private
-   */
-  tracking.ColorTracker.prototype.getNeighboursForWidth_ = function(width) {
-    if (tracking.ColorTracker.neighbours_[width]) {
-      return tracking.ColorTracker.neighbours_[width];
-    }
-
-    var neighbours = new Int32Array(8);
-
-    neighbours[0] = -width * 4;
-    neighbours[1] = -width * 4 + 4;
-    neighbours[2] = 4;
-    neighbours[3] = width * 4 + 4;
-    neighbours[4] = width * 4;
-    neighbours[5] = width * 4 - 4;
-    neighbours[6] = -4;
-    neighbours[7] = -width * 4 - 4;
-
-    tracking.ColorTracker.neighbours_[width] = neighbours;
-
-    return neighbours;
-  };
-
-  /**
-   * Unites groups whose bounding box intersect with each other.
-   * @param {Array.<Object>} rects
-   * @private
-   */
-  tracking.ColorTracker.prototype.mergeRectangles_ = function(rects) {
-    var intersects;
-    var results = [];
-    var minDimension = this.getMinDimension();
-    var maxDimension = this.getMaxDimension();
-
-    for (var r = 0; r < rects.length; r++) {
-      var r1 = rects[r];
-      intersects = true;
-      for (var s = r + 1; s < rects.length; s++) {
-        var r2 = rects[s];
-        if (tracking.Math.intersectRect(r1.x, r1.y, r1.x + r1.width, r1.y + r1.height, r2.x, r2.y, r2.x + r2.width, r2.y + r2.height)) {
-          intersects = false;
-          var x1 = Math.min(r1.x, r2.x);
-          var y1 = Math.min(r1.y, r2.y);
-          var x2 = Math.max(r1.x + r1.width, r2.x + r2.width);
-          var y2 = Math.max(r1.y + r1.height, r2.y + r2.height);
-          r2.height = y2 - y1;
-          r2.width = x2 - x1;
-          r2.x = x1;
-          r2.y = y1;
-          break;
-        }
-      }
-
-      if (intersects) {
-        if (r1.width >= minDimension && r1.height >= minDimension) {
-          if (r1.width <= maxDimension && r1.height <= maxDimension) {
-            results.push(r1);
-          }
-        }
-      }
-    }
-
-    return results;
-  };
-
-  /**
-   * Sets the colors to be tracked by the `ColorTracker` instance.
-   * @param {Array.<string>} colors
-   */
-  tracking.ColorTracker.prototype.setColors = function(colors) {
-    this.colors = colors;
-  };
-
-  /**
-   * Sets the minimum dimension to classify a rectangle.
-   * @param {number} minDimension
-   */
-  tracking.ColorTracker.prototype.setMinDimension = function(minDimension) {
-    this.minDimension = minDimension;
-  };
-
-  /**
-   * Sets the maximum dimension to classify a rectangle.
-   * @param {number} maxDimension
-   */
-  tracking.ColorTracker.prototype.setMaxDimension = function(maxDimension) {
-    this.maxDimension = maxDimension;
-  };
-
-  /**
-   * Sets the minimum group size to be classified as a rectangle.
-   * @param {number} minGroupSize
-   */
-  tracking.ColorTracker.prototype.setMinGroupSize = function(minGroupSize) {
-    this.minGroupSize = minGroupSize;
-  };
-
-  /**
-   * Tracks the `Video` frames. This method is called for each video frame in
-   * order to emit `track` event.
-   * @param {Uint8ClampedArray} pixels The pixels data to track.
-   * @param {number} width The pixels canvas width.
-   * @param {number} height The pixels canvas height.
-   */
-  tracking.ColorTracker.prototype.track = function(pixels, width, height) {
-    var self = this;
-    var colors = this.getColors();
-
-    if (!colors) {
-      throw new Error('Colors not specified, try `new tracking.ColorTracker("magenta")`.');
-    }
-
-    var results = [];
-
-    colors.forEach(function(color) {
-      results = results.concat(self.trackColor_(pixels, width, height, color));
-    });
-
-    this.emit('track', {
-      data: results
-    });
-  };
-
-  /**
-   * Find the given color in the given matrix of pixels using Flood fill
-   * algorithm to determines the area connected to a given node in a
-   * multi-dimensional array.
-   * @param {Uint8ClampedArray} pixels The pixels data to track.
-   * @param {number} width The pixels canvas width.
-   * @param {number} height The pixels canvas height.
-   * @param {string} color The color to be found
-   * @private
-   */
-  tracking.ColorTracker.prototype.trackColor_ = function(pixels, width, height, color) {
-    var colorFn = tracking.ColorTracker.knownColors_[color];
-    var currGroup = new Int32Array(pixels.length >> 2);
-    var currGroupSize;
-    var currI;
-    var currJ;
-    var currW;
-    var marked = new Int8Array(pixels.length);
-    var minGroupSize = this.getMinGroupSize();
-    var neighboursW = this.getNeighboursForWidth_(width);
-    var queue = new Int32Array(pixels.length);
-    var queuePosition;
-    var results = [];
-    var w = -4;
-
-    if (!colorFn) {
-      return results;
-    }
-
-    for (var i = 0; i < height; i++) {
-      for (var j = 0; j < width; j++) {
-        w += 4;
-
-        if (marked[w]) {
-          continue;
-        }
-
-        currGroupSize = 0;
-
-        queuePosition = -1;
-        queue[++queuePosition] = w;
-        queue[++queuePosition] = i;
-        queue[++queuePosition] = j;
-
-        marked[w] = 1;
-
-        while (queuePosition >= 0) {
-          currJ = queue[queuePosition--];
-          currI = queue[queuePosition--];
-          currW = queue[queuePosition--];
-
-          if (colorFn(pixels[currW], pixels[currW + 1], pixels[currW + 2], pixels[currW + 3], currW, currI, currJ)) {
-            currGroup[currGroupSize++] = currJ;
-            currGroup[currGroupSize++] = currI;
-
-            for (var k = 0; k < neighboursW.length; k++) {
-              var otherW = currW + neighboursW[k];
-              var otherI = currI + neighboursI[k];
-              var otherJ = currJ + neighboursJ[k];
-              if (!marked[otherW] && otherI >= 0 && otherI < height && otherJ >= 0 && otherJ < width) {
-                queue[++queuePosition] = otherW;
-                queue[++queuePosition] = otherI;
-                queue[++queuePosition] = otherJ;
-
-                marked[otherW] = 1;
-              }
-            }
-          }
-        }
-
-        if (currGroupSize >= minGroupSize) {
-          var data = this.calculateDimensions_(currGroup, currGroupSize);
-          if (data) {
-            data.color = color;
-            results.push(data);
-          }
-        }
-      }
-    }
-
-    return this.mergeRectangles_(results);
-  };
-
-  // Default colors
-  //===================
-
-  tracking.ColorTracker.registerColor('cyan', function(r, g, b) {
-    var thresholdGreen = 50,
-      thresholdBlue = 70,
-      dx = r - 0,
-      dy = g - 255,
-      dz = b - 255;
-
-    if ((g - r) >= thresholdGreen && (b - r) >= thresholdBlue) {
-      return true;
-    }
-    return dx * dx + dy * dy + dz * dz < 6400;
-  });
-
-  tracking.ColorTracker.registerColor('magenta', function(r, g, b) {
-    var threshold = 50,
-      dx = r - 255,
-      dy = g - 0,
-      dz = b - 255;
-
-    if ((r - g) >= threshold && (b - g) >= threshold) {
-      return true;
-    }
-    return dx * dx + dy * dy + dz * dz < 19600;
-  });
-
-  tracking.ColorTracker.registerColor('yellow', function(r, g, b) {
-    var threshold = 50,
-      dx = r - 255,
-      dy = g - 255,
-      dz = b - 0;
-
-    if ((r - b) >= threshold && (g - b) >= threshold) {
-      return true;
-    }
-    return dx * dx + dy * dy + dz * dz < 10000;
-  });
-
-
-  // Caching neighbour i/j offset values.
-  //=====================================
-  var neighboursI = new Int32Array([-1, -1, 0, 1, 1, 1, 0, -1]);
-  var neighboursJ = new Int32Array([0, 1, 1, 1, 0, -1, -1, -1]);
-}());

common/tracking.js/src/trackers/LandmarksTracker.js

@@ -1,35 +0,0 @@
-(function() {
-
-
-  tracking.LandmarksTracker = function() {
-    tracking.LandmarksTracker.base(this, 'constructor');
-  }
-
-  tracking.inherits(tracking.LandmarksTracker, tracking.ObjectTracker);
-
-  tracking.LandmarksTracker.prototype.track = function(pixels, width, height) {
-	 
-    var image = {
-      'data': pixels,
-      'width': width,
-      'height': height
-    };
-
-    var classifier = tracking.ViolaJones.classifiers['face'];
-
-    var faces = tracking.ViolaJones.detect(pixels, width, height, 
-      this.getInitialScale(), this.getScaleFactor(), this.getStepSize(), 
-      this.getEdgesDensity(), classifier);
-
-    var landmarks = tracking.LBF.align(pixels, width, height, faces);
-
-    this.emit('track', {
-      'data': {
-        'faces' : faces,
-        'landmarks' : landmarks
-      }
-    });
-
-  }
-
-}());

common/tracking.js/src/trackers/ObjectTracker.js

@@ -1,169 +0,0 @@
-(function() {
-  /**
-   * ObjectTracker utility.
-   * @constructor
-   * @param {string|Array.<string|Array.<number>>} opt_classifiers Optional
-   *     object classifiers to track.
-   * @extends {tracking.Tracker}
-   */
-  tracking.ObjectTracker = function(opt_classifiers) {
-    tracking.ObjectTracker.base(this, 'constructor');
-
-    if (opt_classifiers) {
-      if (!Array.isArray(opt_classifiers)) {
-        opt_classifiers = [opt_classifiers];
-      }
-
-      if (Array.isArray(opt_classifiers)) {
-        opt_classifiers.forEach(function(classifier, i) {
-          if (typeof classifier === 'string') {
-            opt_classifiers[i] = tracking.ViolaJones.classifiers[classifier];
-          }
-          if (!opt_classifiers[i]) {
-            throw new Error('Object classifier not valid, try `new tracking.ObjectTracker("face")`.');
-          }
-        });
-      }
-    }
-
-    this.setClassifiers(opt_classifiers);
-  };
-
-  tracking.inherits(tracking.ObjectTracker, tracking.Tracker);
-
-  /**
-   * Specifies the edges density of a block in order to decide whether to skip
-   * it or not.
-   * @default 0.2
-   * @type {number}
-   */
-  tracking.ObjectTracker.prototype.edgesDensity = 0.2;
-
-  /**
-   * Specifies the initial scale to start the feature block scaling.
-   * @default 1.0
-   * @type {number}
-   */
-  tracking.ObjectTracker.prototype.initialScale = 1.0;
-
-  /**
-   * Specifies the scale factor to scale the feature block.
-   * @default 1.25
-   * @type {number}
-   */
-  tracking.ObjectTracker.prototype.scaleFactor = 1.25;
-
-  /**
-   * Specifies the block step size.
-   * @default 1.5
-   * @type {number}
-   */
-  tracking.ObjectTracker.prototype.stepSize = 1.5;
-
-  /**
-   * Gets the tracker HAAR classifiers.
-   * @return {TypedArray.<number>}
-   */
-  tracking.ObjectTracker.prototype.getClassifiers = function() {
-    return this.classifiers;
-  };
-
-  /**
-   * Gets the edges density value.
-   * @return {number}
-   */
-  tracking.ObjectTracker.prototype.getEdgesDensity = function() {
-    return this.edgesDensity;
-  };
-
-  /**
-   * Gets the initial scale to start the feature block scaling.
-   * @return {number}
-   */
-  tracking.ObjectTracker.prototype.getInitialScale = function() {
-    return this.initialScale;
-  };
-
-  /**
-   * Gets the scale factor to scale the feature block.
-   * @return {number}
-   */
-  tracking.ObjectTracker.prototype.getScaleFactor = function() {
-    return this.scaleFactor;
-  };
-
-  /**
-   * Gets the block step size.
-   * @return {number}
-   */
-  tracking.ObjectTracker.prototype.getStepSize = function() {
-    return this.stepSize;
-  };
-
-  /**
-   * Tracks the `Video` frames. This method is called for each video frame in
-   * order to emit `track` event.
-   * @param {Uint8ClampedArray} pixels The pixels data to track.
-   * @param {number} width The pixels canvas width.
-   * @param {number} height The pixels canvas height.
-   */
-  tracking.ObjectTracker.prototype.track = function(pixels, width, height) {
-    var self = this;
-    var classifiers = this.getClassifiers();
-
-    if (!classifiers) {
-      throw new Error('Object classifier not specified, try `new tracking.ObjectTracker("face")`.');
-    }
-
-    var results = [];
-
-    classifiers.forEach(function(classifier) {
-      results = results.concat(tracking.ViolaJones.detect(pixels, width, height, self.getInitialScale(), self.getScaleFactor(), self.getStepSize(), self.getEdgesDensity(), classifier));
-    });
-
-    this.emit('track', {
-      data: results
-    });
-  };
-
-  /**
-   * Sets the tracker HAAR classifiers.
-   * @param {TypedArray.<number>} classifiers
-   */
-  tracking.ObjectTracker.prototype.setClassifiers = function(classifiers) {
-    this.classifiers = classifiers;
-  };
-
-  /**
-   * Sets the edges density.
-   * @param {number} edgesDensity
-   */
-  tracking.ObjectTracker.prototype.setEdgesDensity = function(edgesDensity) {
-    this.edgesDensity = edgesDensity;
-  };
-
-  /**
-   * Sets the initial scale to start the block scaling.
-   * @param {number} initialScale
-   */
-  tracking.ObjectTracker.prototype.setInitialScale = function(initialScale) {
-    this.initialScale = initialScale;
-  };
-
-  /**
-   * Sets the scale factor to scale the feature block.
-   * @param {number} scaleFactor
-   */
-  tracking.ObjectTracker.prototype.setScaleFactor = function(scaleFactor) {
-    this.scaleFactor = scaleFactor;
-  };
-
-  /**
-   * Sets the block step size.
-   * @param {number} stepSize
-   */
-  tracking.ObjectTracker.prototype.setStepSize = function(stepSize) {
-    this.stepSize = stepSize;
-  };
-
-}());

common/tracking.js/src/trackers/Tracker.js

@@ -1,21 +0,0 @@
-(function() {
-  /**
-   * Tracker utility.
-   * @constructor
-   * @extends {tracking.EventEmitter}
-   */
-  tracking.Tracker = function() {
-    tracking.Tracker.base(this, 'constructor');
-  };
-
-  tracking.inherits(tracking.Tracker, tracking.EventEmitter);
-
-  /**
-   * Tracks the pixels on the array. This method is called for each video
-   * frame in order to emit `track` event.
-   * @param {Uint8ClampedArray} pixels The pixels data to track.
-   * @param {number} width The pixels canvas width.
-   * @param {number} height The pixels canvas height.
-   */
-  tracking.Tracker.prototype.track = function() {};
-}());

common/tracking.js/src/trackers/TrackerTask.js

@@ -1,103 +0,0 @@
-(function() {
-  /**
-   * TrackerTask utility.
-   * @constructor
-   * @extends {tracking.EventEmitter}
-   */
-  tracking.TrackerTask = function(tracker) {
-    tracking.TrackerTask.base(this, 'constructor');
-
-    if (!tracker) {
-      throw new Error('Tracker instance not specified.');
-    }
-
-    this.setTracker(tracker);
-  };
-
-  tracking.inherits(tracking.TrackerTask, tracking.EventEmitter);
-
-  /**
-   * Holds the tracker instance managed by this task.
-   * @type {tracking.Tracker}
-   * @private
-   */
-  tracking.TrackerTask.prototype.tracker_ = null;
-
-  /**
-   * Holds if the tracker task is in running.
-   * @type {boolean}
-   * @private
-   */
-  tracking.TrackerTask.prototype.running_ = false;
-
-  /**
-   * Gets the tracker instance managed by this task.
-   * @return {tracking.Tracker}
-   */
-  tracking.TrackerTask.prototype.getTracker = function() {
-    return this.tracker_;
-  };
-
-  /**
-   * Returns true if the tracker task is in running, false otherwise.
-   * @return {boolean}
-   * @private
-   */
-  tracking.TrackerTask.prototype.inRunning = function() {
-    return this.running_;
-  };
-
-  /**
-   * Sets if the tracker task is in running.
-   * @param {boolean} running
-   * @private
-   */
-  tracking.TrackerTask.prototype.setRunning = function(running) {
-    this.running_ = running;
-  };
-
-  /**
-   * Sets the tracker instance managed by this task.
-   * @return {tracking.Tracker}
-   */
-  tracking.TrackerTask.prototype.setTracker = function(tracker) {
-    this.tracker_ = tracker;
-  };
-
-  /**
-   * Emits a `run` event on the tracker task for the implementers to run any
-   * child action, e.g. `requestAnimationFrame`.
-   * @return {object} Returns itself, so calls can be chained.
-   */
-  tracking.TrackerTask.prototype.run = function() {
-    var self = this;
-
-    if (this.inRunning()) {
-      return;
-    }
-
-    this.setRunning(true);
-    this.reemitTrackEvent_ = function(event) {
-      self.emit('track', event);
-    };
-    this.tracker_.on('track', this.reemitTrackEvent_);
-    this.emit('run');
-    return this;
-  };
-
-  /**
-   * Emits a `stop` event on the tracker task for the implementers to stop any
-   * child action being done, e.g. `requestAnimationFrame`.
-   * @return {object} Returns itself, so calls can be chained.
-   */
-  tracking.TrackerTask.prototype.stop = function() {
-    if (!this.inRunning()) {
-      return;
-    }
-
-    this.setRunning(false);
-    this.emit('stop');
-    this.tracker_.removeListener('track', this.reemitTrackEvent_);
-    return this;
-  };
-}());

common/tracking.js/src/tracking.js

@@ -1,285 +0,0 @@
-(function(window, undefined) {
-  window.tracking = window.tracking || {};
-
-  /**
-   * Inherit the prototype methods from one constructor into another.
-   *
-   * Usage:
-   * <pre>
-   * function ParentClass(a, b) { }
-   * ParentClass.prototype.foo = function(a) { }
-   *
-   * function ChildClass(a, b, c) {
-   *   tracking.base(this, a, b);
-   * }
-   * tracking.inherits(ChildClass, ParentClass);
-   *
-   * var child = new ChildClass('a', 'b', 'c');
-   * child.foo();
-   * </pre>
-   *
-   * @param {Function} childCtor Child class.
-   * @param {Function} parentCtor Parent class.
-   */
-  tracking.inherits = function(childCtor, parentCtor) {
-    function TempCtor() {
-    }
-    TempCtor.prototype = parentCtor.prototype;
-    childCtor.superClass_ = parentCtor.prototype;
-    childCtor.prototype = new TempCtor();
-    childCtor.prototype.constructor = childCtor;
-
-    /**
-     * Calls superclass constructor/method.
-     *
-     * This function is only available if you use tracking.inherits to express
-     * inheritance relationships between classes.
-     *
-     * @param {!object} me Should always be "this".
-     * @param {string} methodName The method name to call. Calling superclass
-     *     constructor can be done with the special string 'constructor'.
-     * @param {...*} var_args The arguments to pass to superclass
-     *     method/constructor.
-     * @return {*} The return value of the superclass method/constructor.
-     */
-    childCtor.base = function(me, methodName) {
-      var args = Array.prototype.slice.call(arguments, 2);
-      return parentCtor.prototype[methodName].apply(me, args);
-    };
-  };
-
-  /**
-   * Captures the user camera when tracking a video element and set its source
-   * to the camera stream.
-   * @param {HTMLVideoElement} element Canvas element to track.
-   * @param {object} opt_options Optional configuration to the tracker.
-   */
-  tracking.initUserMedia_ = function(element, opt_options) {
-    window.navigator.mediaDevices.getUserMedia({
-      video: true,
-      audio: (opt_options && opt_options.audio) ? true : false,
-    }).then(function(stream) {
-      element.srcObject = stream;
-    }).catch(function(err) {
-      throw Error('Cannot capture user camera.');
-    });
-  };
-
-  /**
-   * Tests whether the object is a dom node.
-   * @param {object} o Object to be tested.
-   * @return {boolean} True if the object is a dom node.
-   */
-  tracking.isNode = function(o) {
-    return o.nodeType || this.isWindow(o);
-  };
-
-  /**
-   * Tests whether the object is the `window` object.
-   * @param {object} o Object to be tested.
-   * @return {boolean} True if the object is the `window` object.
-   */
-  tracking.isWindow = function(o) {
-    return !!(o && o.alert && o.document);
-  };
-
-  /**
-   * Selects a dom node from a CSS3 selector using `document.querySelector`.
-   * @param {string} selector
-   * @param {object} opt_element The root element for the query. When not
-   *     specified `document` is used as root element.
-   * @return {HTMLElement} The first dom element that matches to the selector.
-   *     If not found, returns `null`.
-   */
-  tracking.one = function(selector, opt_element) {
-    if (this.isNode(selector)) {
-      return selector;
-    }
-    return (opt_element || document).querySelector(selector);
-  };
-
-  /**
-   * Tracks a canvas, image or video element based on the specified `tracker`
-   * instance. This method extract the pixel information of the input element
-   * to pass to the `tracker` instance. When tracking a video, the
-   * `tracker.track(pixels, width, height)` will be in a
-   * `requestAnimationFrame` loop in order to track all video frames.
-   *
-   * Example:
-   * var tracker = new tracking.ColorTracker();
-   *
-   * tracking.track('#video', tracker);
-   * or
-   * tracking.track('#video', tracker, { camera: true });
-   *
-   * tracker.on('track', function(event) {
-   *   // console.log(event.data[0].x, event.data[0].y)
-   * });
-   *
-   * @param {HTMLElement} element The element to track, canvas, image or
-   *     video.
-   * @param {tracking.Tracker} tracker The tracker instance used to track the
-   *     element.
-   * @param {object} opt_options Optional configuration to the tracker.
-   */
-  tracking.track = function(element, tracker, opt_options) {
-    element = tracking.one(element);
-    if (!element) {
-      throw new Error('Element not found, try a different element or selector.');
-    }
-    if (!tracker) {
-      throw new Error('Tracker not specified, try `tracking.track(element, new tracking.FaceTracker())`.');
-    }
-
-    switch (element.nodeName.toLowerCase()) {
-      case 'canvas':
-        return this.trackCanvas_(element, tracker, opt_options);
-      case 'img':
-        return this.trackImg_(element, tracker, opt_options);
-      case 'video':
-        if (opt_options) {
-          if (opt_options.camera) {
-            this.initUserMedia_(element, opt_options);
-          }
-        }
-        return this.trackVideo_(element, tracker, opt_options);
-      default:
-        throw new Error('Element not supported, try in a canvas, img, or video.');
-    }
-  };
-
-  /**
-   * Tracks a canvas element based on the specified `tracker` instance and
-   * returns a `TrackerTask` for this track.
-   * @param {HTMLCanvasElement} element Canvas element to track.
-   * @param {tracking.Tracker} tracker The tracker instance used to track the
-   *     element.
-   * @param {object} opt_options Optional configuration to the tracker.
-   * @return {tracking.TrackerTask}
-   * @private
-   */
-  tracking.trackCanvas_ = function(element, tracker) {
-    var self = this;
-    var task = new tracking.TrackerTask(tracker);
-    task.on('run', function() {
-      self.trackCanvasInternal_(element, tracker);
-    });
-    return task.run();
-  };
-
-  /**
-   * Tracks a canvas element based on the specified `tracker` instance. This
-   * method extract the pixel information of the input element to pass to the
-   * `tracker` instance.
-   * @param {HTMLCanvasElement} element Canvas element to track.
-   * @param {tracking.Tracker} tracker The tracker instance used to track the
-   *     element.
-   * @param {object} opt_options Optional configuration to the tracker.
-   * @private
-   */
-  tracking.trackCanvasInternal_ = function(element, tracker) {
-    var width = element.width;
-    var height = element.height;
-    var context = element.getContext('2d');
-    var imageData = context.getImageData(0, 0, width, height);
-    tracker.track(imageData.data, width, height);
-  };
-
-  /**
-   * Tracks a image element based on the specified `tracker` instance. This
-   * method extract the pixel information of the input element to pass to the
-   * `tracker` instance.
-   * @param {HTMLImageElement} element Canvas element to track.
-   * @param {tracking.Tracker} tracker The tracker instance used to track the
-   *     element.
-   * @param {object} opt_options Optional configuration to the tracker.
-   * @private
-   */
-  tracking.trackImg_ = function(element, tracker) {
-    var width = element.naturalWidth;
-    var height = element.naturalHeight;
-    var canvas = document.createElement('canvas');
-
-    canvas.width = width;
-    canvas.height = height;
-
-    var task = new tracking.TrackerTask(tracker);
-    task.on('run', function() {
-      tracking.Canvas.loadImage(canvas, element.src, 0, 0, width, height, function() {
-        tracking.trackCanvasInternal_(canvas, tracker);
-      });
-    });
-    return task.run();
-  };
-
-  /**
-   * Tracks a video element based on the specified `tracker` instance. This
-   * method extract the pixel information of the input element to pass to the
-   * `tracker` instance. The `tracker.track(pixels, width, height)` will be in
-   * a `requestAnimationFrame` loop in order to track all video frames.
-   * @param {HTMLVideoElement} element Canvas element to track.
-   * @param {tracking.Tracker} tracker The tracker instance used to track the
-   *     element.
-   * @param {object} opt_options Optional configuration to the tracker.
-   * @private
-   */
-  tracking.trackVideo_ = function(element, tracker) {
-    var canvas = document.createElement('canvas');
-    var context = canvas.getContext('2d');
-    var width;
-    var height;
-
-
-// FIXME here the video display size of the analysed size
-    var resizeCanvas_ = function() {
-      width = element.offsetWidth;
-      height = element.offsetHeight;
-      canvas.width = width;
-      canvas.height = height;
-    };
-    resizeCanvas_();
-    element.addEventListener('resize', resizeCanvas_);
-
-
-// FIXME: do a process function - it is up to the caller to handle the frequency of detection
-// it seems all handled in the tracking.TrackerTask..
-// so in short, remove the tracking.TrackerTask from here
-// if the user want to use it, it can create it himself
-    var requestId;
-    var requestAnimationFrame_ = function() {
-      requestId = window.requestAnimationFrame(function() {
-        if (element.readyState === element.HAVE_ENOUGH_DATA) {
-          try {
-            // Firefox v~30.0 gets confused with the video readyState firing an
-            // erroneous HAVE_ENOUGH_DATA just before HAVE_CURRENT_DATA state,
-            // hence keep trying to read it until resolved.
-            context.drawImage(element, 0, 0, width, height);
-          } catch (err) {}
-          tracking.trackCanvasInternal_(canvas, tracker);
-        }
-        requestAnimationFrame_();
-      });
-    };
-
-    var task = new tracking.TrackerTask(tracker);
-    task.on('stop', function() {
-      window.cancelAnimationFrame(requestId);
-    });
-    task.on('run', function() {
-      requestAnimationFrame_();
-    });
-    return task.run();
-  };
-
-  // Browser polyfills
-  //===================
-
-  if (!window.URL) {
-    window.URL = window.URL || window.webkitURL || window.msURL || window.oURL;
-  }
-
-  if (!navigator.getUserMedia) {
-    navigator.getUserMedia = navigator.getUserMedia || navigator.webkitGetUserMedia ||
-    navigator.mozGetUserMedia || navigator.msGetUserMedia;
-  }
-}(window));

common/tracking.js/src/utils/Canvas.js

@@ -1,37 +0,0 @@
-(function() {
-  /**
-   * Canvas utility.
-   * @static
-   * @constructor
-   */
-  tracking.Canvas = {};
-
-  /**
-   * Loads an image source into the canvas.
-   * @param {HTMLCanvasElement} canvas The canvas dom element.
-   * @param {string} src The image source.
-   * @param {number} x The canvas horizontal coordinate to load the image.
-   * @param {number} y The canvas vertical coordinate to load the image.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {function} opt_callback Callback that fires when the image is loaded
-   *     into the canvas.
-   * @static
-   */
-  tracking.Canvas.loadImage = function(canvas, src, x, y, width, height, opt_callback) {
-    var instance = this;
-    var img = new window.Image();
-    img.crossOrigin = '*';
-    img.onload = function() {
-      var context = canvas.getContext('2d');
-      canvas.width = width;
-      canvas.height = height;
-      context.drawImage(img, x, y, width, height);
-      if (opt_callback) {
-        opt_callback.call(instance);
-      }
-      img = null;
-    };
-    img.src = src;
-  };
-}());

common/tracking.js/src/utils/DisjointSet.js

@@ -1,60 +0,0 @@
-(function() {
-  /**
-   * DisjointSet utility with path compression. Some applications involve
-   * grouping n distinct objects into a collection of disjoint sets. Two
-   * important operations are then finding which set a given object belongs to
-   * and uniting the two sets. A disjoint set data structure maintains a
-   * collection S={ S1 , S2 ,..., Sk } of disjoint dynamic sets. Each set is
-   * identified by a representative, which usually is a member in the set.
-   * @static
-   * @constructor
-   */
-  tracking.DisjointSet = function(length) {
-    if (length === undefined) {
-      throw new Error('DisjointSet length not specified.');
-    }
-    this.length = length;
-    this.parent = new Uint32Array(length);
-    for (var i = 0; i < length; i++) {
-      this.parent[i] = i;
-    }
-  };
-
-  /**
-   * Holds the length of the internal set.
-   * @type {number}
-   */
-  tracking.DisjointSet.prototype.length = null;
-
-  /**
-   * Holds the set containing the representative values.
-   * @type {Array.<number>}
-   */
-  tracking.DisjointSet.prototype.parent = null;
-
-  /**
-   * Finds a pointer to the representative of the set containing i.
-   * @param {number} i
-   * @return {number} The representative set of i.
-   */
-  tracking.DisjointSet.prototype.find = function(i) {
-    if (this.parent[i] === i) {
-      return i;
-    } else {
-      return (this.parent[i] = this.find(this.parent[i]));
-    }
-  };
-
-  /**
-   * Unites two dynamic sets containing objects i and j, say Si and Sj, into
-   * a new set that Si ∪ Sj, assuming that Si ∩ Sj = ∅;
-   * @param {number} i
-   * @param {number} j
-   */
-  tracking.DisjointSet.prototype.union = function(i, j) {
-    var iRepresentative = this.find(i);
-    var jRepresentative = this.find(j);
-    this.parent[iRepresentative] = jRepresentative;
-  };
-
-}());

common/tracking.js/src/utils/EventEmitter.js

@@ -1,149 +0,0 @@
-(function() {
-  /**
-   * EventEmitter utility.
-   * @constructor
-   */
-  tracking.EventEmitter = function() {};
-
-  /**
-   * Holds event listeners scoped by event type.
-   * @type {object}
-   * @private
-   */
-  tracking.EventEmitter.prototype.events_ = null;
-
-  /**
-   * Adds a listener to the end of the listeners array for the specified event.
-   * @param {string} event
-   * @param {function} listener
-   * @return {object} Returns emitter, so calls can be chained.
-   */
-  tracking.EventEmitter.prototype.addListener = function(event, listener) {
-    if (typeof listener !== 'function') {
-      throw new TypeError('Listener must be a function');
-    }
-    if (!this.events_) {
-      this.events_ = {};
-    }
-
-    this.emit('newListener', event, listener);
-
-    if (!this.events_[event]) {
-      this.events_[event] = [];
-    }
-
-    this.events_[event].push(listener);
-
-    return this;
-  };
-
-  /**
-   * Returns an array of listeners for the specified event.
-   * @param {string} event
-   * @return {array} Array of listeners.
-   */
-  tracking.EventEmitter.prototype.listeners = function(event) {
-    return this.events_ && this.events_[event];
-  };
-
-  /**
-   * Execute each of the listeners in order with the supplied arguments.
-   * @param {string} event
-   * @param {*} opt_args [arg1], [arg2], [...]
-   * @return {boolean} Returns true if event had listeners, false otherwise.
-   */
-  tracking.EventEmitter.prototype.emit = function(event) {
-    var listeners = this.listeners(event);
-    if (listeners) {
-      var args = Array.prototype.slice.call(arguments, 1);
-      for (var i = 0; i < listeners.length; i++) {
-        if (listeners[i]) {
-          listeners[i].apply(this, args);
-        }
-      }
-      return true;
-    }
-    return false;
-  };
-
-  /**
-   * Adds a listener to the end of the listeners array for the specified event.
-   * @param {string} event
-   * @param {function} listener
-   * @return {object} Returns emitter, so calls can be chained.
-   */
-  tracking.EventEmitter.prototype.on = tracking.EventEmitter.prototype.addListener;
-
-  /**
-   * Adds a one time listener for the event. This listener is invoked only the
-   * next time the event is fired, after which it is removed.
-   * @param {string} event
-   * @param {function} listener
-   * @return {object} Returns emitter, so calls can be chained.
-   */
-  tracking.EventEmitter.prototype.once = function(event, listener) {
-    var self = this;
-    self.on(event, function handlerInternal() {
-      self.removeListener(event, handlerInternal);
-      listener.apply(this, arguments);
-    });
-  };
-
-  /**
-   * Removes all listeners, or those of the specified event. It's not a good
-   * idea to remove listeners that were added elsewhere in the code,
-   * especially when it's on an emitter that you didn't create.
-   * @param {string} event
-   * @return {object} Returns emitter, so calls can be chained.
-   */
-  tracking.EventEmitter.prototype.removeAllListeners = function(opt_event) {
-    if (!this.events_) {
-      return this;
-    }
-    if (opt_event) {
-      delete this.events_[opt_event];
-    } else {
-      delete this.events_;
-    }
-    return this;
-  };
-
-  /**
-   * Remove a listener from the listener array for the specified event.
-   * Caution: changes array indices in the listener array behind the listener.
-   * @param {string} event
-   * @param {function} listener
-   * @return {object} Returns emitter, so calls can be chained.
-   */
-  tracking.EventEmitter.prototype.removeListener = function(event, listener) {
-    if (typeof listener !== 'function') {
-      throw new TypeError('Listener must be a function');
-    }
-    if (!this.events_) {
-      return this;
-    }
-
-    var listeners = this.listeners(event);
-    if (Array.isArray(listeners)) {
-      var i = listeners.indexOf(listener);
-      if (i < 0) {
-        return this;
-      }
-      listeners.splice(i, 1);
-    }
-
-    return this;
-  };
-
-  /**
-   * By default EventEmitters will print a warning if more than 10 listeners
-   * are added for a particular event. This is a useful default which helps
-   * finding memory leaks. Obviously not all Emitters should be limited to 10.
-   * This function allows that to be increased. Set to zero for unlimited.
-   * @param {number} n The maximum number of listeners.
-   */
-  tracking.EventEmitter.prototype.setMaxListeners = function() {
-    throw new Error('Not implemented');
-  };
-
-}());

common/tracking.js/src/utils/Image.js

@@ -1,392 +0,0 @@
-(function() {
-  /**
-   * Image utility.
-   * @static
-   * @constructor
-   */
-  tracking.Image = {};
-
-  /**
-   * Computes gaussian blur. Adapted from
-   * https://github.com/kig/canvasfilters.
-   * @param {pixels} pixels The pixels in a linear [r,g,b,a,...] array.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {number} diameter Gaussian blur diameter, must be greater than 1.
-   * @return {array} The edge pixels in a linear [r,g,b,a,...] array.
-   */
-  tracking.Image.blur = function(pixels, width, height, diameter) {
-    diameter = Math.abs(diameter);
-    if (diameter <= 1) {
-      throw new Error('Diameter should be greater than 1.');
-    }
-    var radius = diameter / 2;
-    var len = Math.ceil(diameter) + (1 - (Math.ceil(diameter) % 2));
-    var weights = new Float32Array(len);
-    var rho = (radius + 0.5) / 3;
-    var rhoSq = rho * rho;
-    var gaussianFactor = 1 / Math.sqrt(2 * Math.PI * rhoSq);
-    var rhoFactor = -1 / (2 * rho * rho);
-    var wsum = 0;
-    var middle = Math.floor(len / 2);
-    for (var i = 0; i < len; i++) {
-      var x = i - middle;
-      var gx = gaussianFactor * Math.exp(x * x * rhoFactor);
-      weights[i] = gx;
-      wsum += gx;
-    }
-    for (var j = 0; j < weights.length; j++) {
-      weights[j] /= wsum;
-    }
-    return this.separableConvolve(pixels, width, height, weights, weights, false);
-  };
-
-  /**
-   * Computes the integral image for summed, squared, rotated and sobel pixels.
-   * @param {array} pixels The pixels in a linear [r,g,b,a,...] array to loop
-   *     through.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {array} opt_integralImage Empty array of size `width * height` to
-   *     be filled with the integral image values. If not specified compute sum
-   *     values will be skipped.
-   * @param {array} opt_integralImageSquare Empty array of size `width *
-   *     height` to be filled with the integral image squared values. If not
-   *     specified compute squared values will be skipped.
-   * @param {array} opt_tiltedIntegralImage Empty array of size `width *
-   *     height` to be filled with the rotated integral image values. If not
-   *     specified compute sum values will be skipped.
-   * @param {array} opt_integralImageSobel Empty array of size `width *
-   *     height` to be filled with the integral image of sobel values. If not
-   *     specified compute sobel filtering will be skipped.
-   * @static
-   */
-  tracking.Image.computeIntegralImage = function(pixels, width, height, opt_integralImage, opt_integralImageSquare, opt_tiltedIntegralImage, opt_integralImageSobel) {
-    if (arguments.length < 4) {
-      throw new Error('You should specify at least one output array in the order: sum, square, tilted, sobel.');
-    }
-    var pixelsSobel;
-    if (opt_integralImageSobel) {
-      pixelsSobel = tracking.Image.sobel(pixels, width, height);
-    }
-    for (var i = 0; i < height; i++) {
-      for (var j = 0; j < width; j++) {
-        var w = i * width * 4 + j * 4;
-        var pixel = ~~(pixels[w] * 0.299 + pixels[w + 1] * 0.587 + pixels[w + 2] * 0.114);
-        if (opt_integralImage) {
-          this.computePixelValueSAT_(opt_integralImage, width, i, j, pixel);
-        }
-        if (opt_integralImageSquare) {
-          this.computePixelValueSAT_(opt_integralImageSquare, width, i, j, pixel * pixel);
-        }
-        if (opt_tiltedIntegralImage) {
-          var w1 = w - width * 4;
-          var pixelAbove = ~~(pixels[w1] * 0.299 + pixels[w1 + 1] * 0.587 + pixels[w1 + 2] * 0.114);
-          this.computePixelValueRSAT_(opt_tiltedIntegralImage, width, i, j, pixel, pixelAbove || 0);
-        }
-        if (opt_integralImageSobel) {
-          this.computePixelValueSAT_(opt_integralImageSobel, width, i, j, pixelsSobel[w]);
-        }
-      }
-    }
-  };
-
-  /**
-   * Helper method to compute the rotated summed area table (RSAT) by the
-   * formula:
-   *
-   * RSAT(x, y) = RSAT(x-1, y-1) + RSAT(x+1, y-1) - RSAT(x, y-2) + I(x, y) + I(x, y-1)
-   *
-   * @param {number} width The image width.
-   * @param {array} RSAT Empty array of size `width * height` to be filled with
-   *     the integral image values. If not specified compute sum values will be
-   *     skipped.
-   * @param {number} i Vertical position of the pixel to be evaluated.
-   * @param {number} j Horizontal position of the pixel to be evaluated.
-   * @param {number} pixel Pixel value to be added to the integral image.
-   * @static
-   * @private
-   */
-  tracking.Image.computePixelValueRSAT_ = function(RSAT, width, i, j, pixel, pixelAbove) {
-    var w = i * width + j;
-    RSAT[w] = (RSAT[w - width - 1] || 0) + (RSAT[w - width + 1] || 0) - (RSAT[w - width - width] || 0) + pixel + pixelAbove;
-  };
-
-  /**
-   * Helper method to compute the summed area table (SAT) by the formula:
-   *
-   * SAT(x, y) = SAT(x, y-1) + SAT(x-1, y) + I(x, y) - SAT(x-1, y-1)
-   *
-   * @param {number} width The image width.
-   * @param {array} SAT Empty array of size `width * height` to be filled with
-   *     the integral image values. If not specified compute sum values will be
-   *     skipped.
-   * @param {number} i Vertical position of the pixel to be evaluated.
-   * @param {number} j Horizontal position of the pixel to be evaluated.
-   * @param {number} pixel Pixel value to be added to the integral image.
-   * @static
-   * @private
-   */
-  tracking.Image.computePixelValueSAT_ = function(SAT, width, i, j, pixel) {
-    var w = i * width + j;
-    SAT[w] = (SAT[w - width] || 0) + (SAT[w - 1] || 0) + pixel - (SAT[w - width - 1] || 0);
-  };
-
-  /**
-   * Converts a color from a color-space based on an RGB color model to a
-   * grayscale representation of its luminance. The coefficients represent the
-   * measured intensity perception of typical trichromat humans, in
-   * particular, human vision is most sensitive to green and least sensitive
-   * to blue.
-   * @param {Uint8Array|Uint8ClampedArray|Array} pixels The pixels in a linear [r,g,b,a,...] array.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {boolean} fillRGBA If the result should fill all RGBA values with the gray scale
-   *  values, instead of returning a single value per pixel.
-   * @return {Uint8Array} The grayscale pixels in a linear array ([p,p,p,a,...] if fillRGBA
-   *  is true and [p1, p2, p3, ...] if fillRGBA is false).
-   * @static
-   */
-  tracking.Image.grayscale = function(pixels, width, height, fillRGBA) {
-
-    /*
-      Performance result (rough EST. - image size, CPU arch. will affect):
-      https://jsperf.com/tracking-new-image-to-grayscale
-
-      Firefox v.60b:
-            fillRGBA  Gray only
-      Old      11       551     OPs/sec
-      New    3548      6487     OPs/sec
-      ---------------------------------
-              322.5x     11.8x  faster
-
-      Chrome v.67b:
-            fillRGBA  Gray only
-      Old     291       489     OPs/sec
-      New    6975      6635     OPs/sec
-      ---------------------------------
-              24.0x      13.6x  faster
-
-      - Ken Nilsen / epistemex
-     */
-
-    var len = pixels.length>>2;
-    var gray = fillRGBA ? new Uint32Array(len) : new Uint8Array(len);
-    var data32 = new Uint32Array(pixels.buffer || new Uint8Array(pixels).buffer);
-    var i = 0;
-    var c = 0;
-    var luma = 0;
-
-    // unrolled loops to not have to check fillRGBA each iteration
-    if (fillRGBA) {
-      while(i < len) {
-        // Entire pixel in little-endian order (ABGR)
-        c = data32[i];
-
-        // Using the more up-to-date REC/BT.709 approx. weights for luma instead: [0.2126, 0.7152, 0.0722].
-        //   luma = ((c>>>16 & 0xff) * 0.2126 + (c>>>8 & 0xff) * 0.7152 + (c & 0xff) * 0.0722 + 0.5)|0;
-        // But I'm using scaled integers here for speed (x 0xffff). This can be improved more using 2^n
-        //   close to the factors allowing for shift-ops (i.e. 4732 -> 4096 => .. (c&0xff) << 12 .. etc.)
-        //   if "accuracy" is not important (luma is anyway an visual approx.):
-        luma = ((c>>>16&0xff) * 13933 + (c>>>8&0xff) * 46871 + (c&0xff) * 4732)>>>16;
-        gray[i++] = luma * 0x10101 | c & 0xff000000;
-      }
-    }
-    else {
-      while(i < len) {
-        c = data32[i];
-        luma = ((c>>>16&0xff) * 13933 + (c>>>8&0xff) * 46871 + (c&0xff) * 4732)>>>16;
-        // ideally, alpha should affect value here: value * (alpha/255) or with shift-ops for the above version
-        gray[i++] = luma;
-      }
-    }
-
-    // Consolidate array view to byte component format independent of source view
-    return new Uint8Array(gray.buffer);
-  };
-
-  /**
-   * Fast horizontal separable convolution. A point spread function (PSF) is
-   * said to be separable if it can be broken into two one-dimensional
-   * signals: a vertical and a horizontal projection. The convolution is
-   * performed by sliding the kernel over the image, generally starting at the
-   * top left corner, so as to move the kernel through all the positions where
-   * the kernel fits entirely within the boundaries of the image. Adapted from
-   * https://github.com/kig/canvasfilters.
-   * @param {pixels} pixels The pixels in a linear [r,g,b,a,...] array.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {array} weightsVector The weighting vector, e.g [-1,0,1].
-   * @param {number} opaque
-   * @return {array} The convoluted pixels in a linear [r,g,b,a,...] array.
-   */
-  tracking.Image.horizontalConvolve = function(pixels, width, height, weightsVector, opaque) {
-    var side = weightsVector.length;
-    var halfSide = Math.floor(side / 2);
-    var output = new Float32Array(width * height * 4);
-    var alphaFac = opaque ? 1 : 0;
-
-    for (var y = 0; y < height; y++) {
-      for (var x = 0; x < width; x++) {
-        var sy = y;
-        var sx = x;
-        var offset = (y * width + x) * 4;
-        var r = 0;
-        var g = 0;
-        var b = 0;
-        var a = 0;
-        for (var cx = 0; cx < side; cx++) {
-          var scy = sy;
-          var scx = Math.min(width - 1, Math.max(0, sx + cx - halfSide));
-          var poffset = (scy * width + scx) * 4;
-          var wt = weightsVector[cx];
-          r += pixels[poffset] * wt;
-          g += pixels[poffset + 1] * wt;
-          b += pixels[poffset + 2] * wt;
-          a += pixels[poffset + 3] * wt;
-        }
-        output[offset] = r;
-        output[offset + 1] = g;
-        output[offset + 2] = b;
-        output[offset + 3] = a + alphaFac * (255 - a);
-      }
-    }
-    return output;
-  };
-
-  /**
-   * Fast vertical separable convolution. A point spread function (PSF) is
-   * said to be separable if it can be broken into two one-dimensional
-   * signals: a vertical and a horizontal projection. The convolution is
-   * performed by sliding the kernel over the image, generally starting at the
-   * top left corner, so as to move the kernel through all the positions where
-   * the kernel fits entirely within the boundaries of the image. Adapted from
-   * https://github.com/kig/canvasfilters.
-   * @param {pixels} pixels The pixels in a linear [r,g,b,a,...] array.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {array} weightsVector The weighting vector, e.g [-1,0,1].
-   * @param {number} opaque
-   * @return {array} The convoluted pixels in a linear [r,g,b,a,...] array.
-   */
-  tracking.Image.verticalConvolve = function(pixels, width, height, weightsVector, opaque) {
-    var side = weightsVector.length;
-    var halfSide = Math.floor(side / 2);
-    var output = new Float32Array(width * height * 4);
-    var alphaFac = opaque ? 1 : 0;
-
-    for (var y = 0; y < height; y++) {
-      for (var x = 0; x < width; x++) {
-        var sy = y;
-        var sx = x;
-        var offset = (y * width + x) * 4;
-        var r = 0;
-        var g = 0;
-        var b = 0;
-        var a = 0;
-        for (var cy = 0; cy < side; cy++) {
-          var scy = Math.min(height - 1, Math.max(0, sy + cy - halfSide));
-          var scx = sx;
-          var poffset = (scy * width + scx) * 4;
-          var wt = weightsVector[cy];
-          r += pixels[poffset] * wt;
-          g += pixels[poffset + 1] * wt;
-          b += pixels[poffset + 2] * wt;
-          a += pixels[poffset + 3] * wt;
-        }
-        output[offset] = r;
-        output[offset + 1] = g;
-        output[offset + 2] = b;
-        output[offset + 3] = a + alphaFac * (255 - a);
-      }
-    }
-    return output;
-  };
-
-  /**
-   * Fast separable convolution. A point spread function (PSF) is said to be
-   * separable if it can be broken into two one-dimensional signals: a
-   * vertical and a horizontal projection. The convolution is performed by
-   * sliding the kernel over the image, generally starting at the top left
-   * corner, so as to move the kernel through all the positions where the
-   * kernel fits entirely within the boundaries of the image. Adapted from
-   * https://github.com/kig/canvasfilters.
-   * @param {pixels} pixels The pixels in a linear [r,g,b,a,...] array.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @param {array} horizWeights The horizontal weighting vector, e.g [-1,0,1].
-   * @param {array} vertWeights The vertical vector, e.g [-1,0,1].
-   * @param {number} opaque
-   * @return {array} The convoluted pixels in a linear [r,g,b,a,...] array.
-   */
-  tracking.Image.separableConvolve = function(pixels, width, height, horizWeights, vertWeights, opaque) {
-    var vertical = this.verticalConvolve(pixels, width, height, vertWeights, opaque);
-    return this.horizontalConvolve(vertical, width, height, horizWeights, opaque);
-  };
-
-  /**
-   * Compute image edges using Sobel operator. Computes the vertical and
-   * horizontal gradients of the image and combines the computed images to
-   * find edges in the image. The way we implement the Sobel filter here is by
-   * first grayscaling the image, then taking the horizontal and vertical
-   * gradients and finally combining the gradient images to make up the final
-   * image. Adapted from https://github.com/kig/canvasfilters.
-   * @param {pixels} pixels The pixels in a linear [r,g,b,a,...] array.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @return {array} The edge pixels in a linear [r,g,b,a,...] array.
-   */
-  tracking.Image.sobel = function(pixels, width, height) {
-    pixels = this.grayscale(pixels, width, height, true);
-    var output = new Float32Array(width * height * 4);
-    var sobelSignVector = new Float32Array([-1, 0, 1]);
-    var sobelScaleVector = new Float32Array([1, 2, 1]);
-    var vertical = this.separableConvolve(pixels, width, height, sobelSignVector, sobelScaleVector);
-    var horizontal = this.separableConvolve(pixels, width, height, sobelScaleVector, sobelSignVector);
-
-    for (var i = 0; i < output.length; i += 4) {
-      var v = vertical[i];
-      var h = horizontal[i];
-      var p = Math.sqrt(h * h + v * v);
-      output[i] = p;
-      output[i + 1] = p;
-      output[i + 2] = p;
-      output[i + 3] = 255;
-    }
-
-    return output;
-  };
-
-  /**
-   * Equalizes the histogram of a grayscale image, normalizing the
-   * brightness and increasing the contrast of the image.
-   * @param {pixels} pixels The grayscale pixels in a linear array.
-   * @param {number} width The image width.
-   * @param {number} height The image height.
-   * @return {array} The equalized grayscale pixels in a linear array.
-   */
-  tracking.Image.equalizeHist = function(pixels, width, height){
-    var equalized = new Uint8ClampedArray(pixels.length);
-
-    var histogram = new Array(256);
-    for(var i=0; i < 256; i++) histogram[i] = 0;
-
-    for(var i=0; i < pixels.length; i++){
-      equalized[i] = pixels[i];
-      histogram[pixels[i]]++;
-    }
-
-    var prev = histogram[0];
-    for(var i=0; i < 256; i++){
-      histogram[i] += prev;
-      prev = histogram[i];
-    }
-
-    var norm = 255 / pixels.length;
-    for(var i=0; i < pixels.length; i++)
-      equalized[i] = (histogram[pixels[i]] * norm + 0.5) | 0;
-
-    return equalized;
-  }
-
-}());

common/tracking.js/test/Benchmark.js

@@ -1,14 +0,0 @@
-var Benchmark = require('./utils/benchmark.js');
-
-module.exports = {
-  setUp: function(done) {
-    Benchmark.setUpAll(done);
-  },
-
-  testBenchmark: function(test) {
-    Benchmark.runAll(function(results) {
-      test.ok(results.passed, Benchmark.createFailureMessage(results.resultDetails));
-      test.done();
-    });
-  }
-};

common/tracking.js/test/Brief.js

@@ -1,76 +0,0 @@
-'use strict';
-
-var tracking = require('./utils/sandbox.js');
-
-module.exports = {
-  setUp: function(done) {
-    done();
-  },
-
-  tearDown: function(done) {
-    done();
-  },
-
-  // TODO: Update this test to generate randomWindowOffsets_ and randomImageOffsets_ instead.
-  testGetDescriptors: function(test) {
-    var descriptors;
-    var descriptorsPerKeypoint = tracking.Brief.N / 32;
-    var grayScale = [
-      0, 0, 1, 0, 0, 0,
-      1, 9, 0, 9, 1, 0,
-      0, 1, 1, 1, 0, 0
-    ];
-    var repeat = [-7, 7, -6, 6, -5, 5, -1, 1];
-    var width = 6;
-
-    // Write the offsets manually, as we can't verify results that are obtained randomly.
-    tracking.Brief.randomImageOffsets_[width] = [];
-    for (var i = 0; i < tracking.Brief.N; i++) {
-      var position = i % 4;
-      tracking.Brief.randomImageOffsets_[width].push(repeat[position * 2], repeat[position * 2 + 1]);
-    }
-
-    descriptors = tracking.Brief.getDescriptors(grayScale, width, [1, 1, 3, 1]);
-
-    test.equal(2 * descriptorsPerKeypoint, descriptors.length, 'There should be 8 descriptor words');
-
-    for (var j = 0; j < descriptorsPerKeypoint; j++) {
-      test.equal(858993459, descriptors[j], 'Descriptor should be 858993459');
-    }
-    for (var k = descriptorsPerKeypoint; k < 2 * descriptorsPerKeypoint; k++) {
-      test.equal(-286331154, descriptors[k], 'Descriptor should be -286331154');
-    }
-
-    test.done();
-  },
-
-  testGetMatchings: function(test) {
-    var descriptors1;
-    var descriptors2;
-    var grayScale1 = [
-      0, 0, 1, 0, 0, 0,
-      1, 9, 0, 9, 1, 0,
-      0, 1, 1, 1, 0, 0
-    ];
-    var grayScale2 = [
-      0, 0, 0, 1, 0, 0,
-      0, 1, 9, 0, 9, 1,
-      0, 0, 1, 1, 1, 0
-    ];
-    var keypoints1 = [1, 1, 3, 1];
-    var keypoints2 = [4, 1, 2, 1];
-    var matchings;
-    var width = 6;
-
-    descriptors1 = tracking.Brief.getDescriptors(grayScale1, width, keypoints1);
-    descriptors2 = tracking.Brief.getDescriptors(grayScale2, width, keypoints2);
-
-    matchings = tracking.Brief.match(keypoints1, descriptors1, keypoints2, descriptors2);
-
-    test.equal(2, matchings.length, 'There should be 2 matchings');
-    test.equal(1, matchings[0].index2, 'Keypoint 0 from 1st array should match keypoint 1 from the 2nd');
-    test.equal(0, matchings[1].index2, 'Keypoint 1 from 1st array should match keypoint 0 from the 2nd');
-
-    test.done();
-  }
-};

common/tracking.js/test/ColorTracker.js

@@ -1,194 +0,0 @@
-'use strict';
-
-var tracking = require('./utils/sandbox.js');
-
-module.exports = {
-  setUp: function(done) {
-    done();
-  },
-
-  tearDown: function(done) {
-    done();
-  },
-
-  testConstructorEmpty: function(test) {
-    var colors;
-    var tracker;
-
-    test.doesNotThrow(function() {
-      tracker = new tracking.ColorTracker();
-    });
-
-    colors = tracker.getColors();
-    test.equal(1, colors.length, 'Colors array should have a single value');
-    test.equal('magenta', colors[0], 'Default color is magenta');
-
-    test.done();
-  },
-
-  testConstructorString: function(test) {
-    var colors;
-    var tracker;
-
-    test.doesNotThrow(function() {
-      tracker = new tracking.ColorTracker('yellow');
-    });
-
-    colors = tracker.getColors();
-    test.equal(1, colors.length, 'Colors array should have a single value');
-    test.equal('yellow', colors[0], 'The colors array should be set to value in the constructor');
-
-    test.throws(function() {
-      tracker = new tracking.ColorTracker('notvalid');
-    });
-
-    test.done();
-  },
-
-  testConstructorArray: function(test) {
-    var colors;
-    var tracker;
-
-    test.doesNotThrow(function() {
-      tracker = new tracking.ColorTracker([]);
-    });
-
-    colors = tracker.getColors();
-    test.equal(0, colors.length, 'Colors array should be empty');
-
-    test.doesNotThrow(function() {
-      tracker = new tracking.ColorTracker(['magenta', 'cyan', 'yellow']);
-    });
-
-    colors = tracker.getColors();
-    test.equal(3, colors.length, 'Colors array have 3 values');
-    test.equal('magenta', colors[0], 'The colors array should be set to values in the constructor');
-    test.equal('cyan', colors[1], 'The colors array should be set to values in the constructor');
-    test.equal('yellow', colors[2], 'The colors array should be set to values in the constructor');
-
-    test.throws(function() {
-      tracker = new tracking.ColorTracker(['magenta', null, 'yellow']);
-    });
-
-    test.done();
-  },
-
-  testFindColor: function(test) {
-    var colors;
-    var pixels;
-    var tracker;
-
-    tracking.ColorTracker.registerColor('black', function(r, g, b) {
-      return r === 0 && g === 0 && b === 0;
-    });
-
-    tracker = new tracking.ColorTracker('black');
-    colors = tracker.getColors();
-
-    test.equal(1, colors.length, 'Colors array have a single value');
-    test.equal('black', colors[0], 'The colors array should be set to values in the constructor');
-
-    tracker.setMinDimension(2);
-    tracker.setMinGroupSize(6);
-
-    pixels = [
-      1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1,
-      1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1,
-      1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1,
-    ];
-
-    tracker.on('track', function(event) {
-      test.equal(1, event.data.length, 'There should only be one result rectangle');
-      test.equal(1, event.data[0].x, 'The first rectangle should be at x = 1');
-      test.equal(0, event.data[0].y, 'The first rectangle should be at y = 0');
-      test.equal(2, event.data[0].width, 'The first rectangle\'s width should be 2');
-      test.equal(3, event.data[0].height, 'The first rectangle\'s height should be 3');
-
-      test.done();
-    });
-
-    tracker.track(pixels, 5, 4);
-  },
-
-  testMergedRectangles: function(test) {
-    var pixels;
-    var tracker;
-
-    tracking.ColorTracker.registerColor('black', function(r, g, b) {
-      return r === 0 && g === 0 && b === 0;
-    });
-
-    tracker = new tracking.ColorTracker('black');
-    tracker.setMinDimension(1);
-    tracker.setMinGroupSize(6);
-
-    pixels = [
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0
-    ];
-
-    tracker.on('track', function(event) {
-      test.equal(2, event.data.length, 'There should be 2 result rectangles');
-      test.equal(0, event.data[0].x, 'The first rectangle should be at x = 0');
-      test.equal(0, event.data[0].y, 'The first rectangle should be at y = 0');
-      test.equal(5, event.data[0].width, 'The first rectangle\'s width should be 5');
-      test.equal(6, event.data[0].height, 'The first rectangle\'s height should be 6');
-      test.equal(2, event.data[1].x, 'The second rectangle should be at x = 2');
-      test.equal(8, event.data[1].y, 'The second rectangle should be at y = 8');
-      test.equal(1, event.data[1].width, 'The second rectangle\'s width should be 1');
-      test.equal(2, event.data[1].height, 'The second rectangle\'s height should be 2');
-
-      test.done();
-    });
-
-    tracker.track(pixels, 6, 11);
-  },
-
-  testDimensionConstraints: function(test) {
-    var pixels;
-    var tracker;
-
-    tracking.ColorTracker.registerColor('black', function(r, g, b) {
-      return r === 0 && g === 0 && b === 0;
-    });
-
-    tracker = new tracking.ColorTracker('black');
-    tracker.setMinDimension(1);
-    tracker.setMaxDimension(2);
-    tracker.setMinGroupSize(6);
-
-    pixels = [
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-      1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
-      0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0
-    ];
-
-    tracker.on('track', function(event) {
-      test.equal(1, event.data.length, 'There should be 1 result rectangle');
-      test.equal(1, event.data[0].width, 'The rectangle\'s width should be 1');
-      test.equal(2, event.data[0].height, 'The rectangle\'s height should be 2');
-
-      test.done();
-    });
-
-    tracker.track(pixels, 6, 11);
-  }
-};

common/tracking.js/test/Fast.js

@@ -1,69 +0,0 @@
-'use strict';
-
-var tracking = require('./utils/sandbox.js');
-
-module.exports = {
-  setUp: function(done) {
-    done();
-  },
-
-  tearDown: function(done) {
-    done();
-  },
-
-  testCornerDetection: function(test) {
-    test.ok(
-      tracking.Fast.isCorner(
-        150,
-        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 255, 255, 255, 255],
-        10
-      ),
-      'A corner should have been detected'
-    );
-
-    test.equal(
-      false,
-      tracking.Fast.isCorner(
-        150,
-        [0, 0, 0, 0, 0, 0, 0, 0, 255, 255, 255, 255, 255, 255, 255, 255],
-        10
-      ),
-      'No corners should have been detected'
-    );
-
-    test.done();
-  },
-
-  testFindCorners: function(test) {
-    var corners,
-      pixels = [];
-
-    for (var i = 0; i < 64; i++) {
-      if (i === 27 || i === 28) {
-        pixels.push(0);
-      }
-      else {
-        pixels.push(255);
-      }
-    }
-
-    corners = tracking.Fast.findCorners(pixels, 8, 8);
-    test.equal(
-      2,
-      corners.length,
-      'Should have found 2 corners'
-    );
-    test.equal(
-      3,
-      corners[0],
-      'Corner should at x = 3'
-    );
-    test.equal(
-      3,
-      corners[1],
-      'Corner should be at y = 3'
-    );
-
-    test.done();
-  }
-};

common/tracking.js/test/ObjectTracker.js

@@ -1,77 +0,0 @@
-'use strict';
-
-var tracking = require('./utils/sandbox.js');
-
-module.exports = {
-  setUp: function(done) {
-    done();
-  },
-
-  tearDown: function(done) {
-    done();
-  },
-
-  testConstructorEmpty: function(test) {
-    test.doesNotThrow(
-      function() {
-        new tracking.ObjectTracker();
-      }
-    );
-
-    test.done();
-  },
-
-  testConstructorClassifier: function(test) {
-    test.doesNotThrow(
-      function() {
-        new tracking.ObjectTracker(tracking.ViolaJones.classifiers.face);
-      }
-    );
-
-    test.done();
-  },
-
-  testConstructorString: function(test) {
-    test.doesNotThrow(
-      function() {
-        new tracking.ObjectTracker('face');
-      }
-    );
-
-    test.throws(
-      function() {
-        new tracking.ObjectTracker('notvalid');
-      }
-    );
-
-    test.done();
-  },
-
-  testConstructorArray: function(test) {
-    test.doesNotThrow(
-      function() {
-        new tracking.ObjectTracker([]);
-      }
-    );
-
-    test.doesNotThrow(
-      function() {
-        new tracking.ObjectTracker([tracking.ViolaJones.classifiers.face]);
-      }
-    );
-
-    test.doesNotThrow(
-      function() {
-        new tracking.ObjectTracker(['face', 'mouth', 'eye']);
-      }
-    );
-
-    test.throws(
-      function() {
-        new tracking.ObjectTracker(['face', null, 'eye']);
-      }
-    );
-
-    test.done();
-  }
-};