Computer Vision for the Web

Foat Akhmadeev

• Publisher: Packt Publishing
• Year: 2015
• eBook ISBN: 9781785886171
• Edition: 1
• Topic: Computer Science
• Subtopic: Programming in JavaScript
• Index: Computer Science

Unleash the power of the Computer Vision algorithms in JavaScript to develop vision-enabled web content

About This Book

• Explore the exciting world of image processing, and face and gesture recognition, and implement them in your website
• Develop wonderful web projects to implement Computer Vision algorithms in an effective way
• A fast-paced guide to help you deal with real-world Computer Vision applications using JavaScript libraries

Who This Book Is For

If you have an interest in Computer Vision or wish to apply Computer Vision algorithms such as face, custom object, and gesture recognition for an online application, then this book is ideal for you. Prior understanding of the JavaScript language and core mathematical concepts is recommended.

What You Will Learn

• Apply complex Computer Vision algorithms in your applications using JavaScript
• Put together different JavaScript libraries to discover objects in photos
• Get to grips with developing simple computer vision applications on your own
• Understand when and why you should use different computer vision methods
• Apply various image filters to images and videos
• Recognize and track many different objects, including face and face particles using powerful face recognition algorithms
• Explore ways to control your browser without touching the mouse or keyboard

In Detail

JavaScript is a dynamic and prototype-based programming language supported by every browser today. JavaScript libraries boast outstanding functionalities that enable you to furnish your own Computer Vision projects, making it easier to develop JavaScript–based applications, especially for web-centric technologies. It makes the implementation of Computer Vision algorithms easier as it supports scheme-based functional programming.

This book will give you an insight into controlling your applications with gestures and head motion and readying them for the web. Packed with real-world tasks, it begins with a walkthrough of the basic concepts of Computer Vision that the JavaScript world offers us, and you'll implement various powerful algorithms in your own online application. Then, we move on to a comprehensive analysis of JavaScript functions and their applications.Furthermore, the book will show you how to implement filters and image segmentation, and use tracking.js and jsfeat libraries to convert your browser into Photoshop. Subjects such as object and custom detection, feature extraction, and object matching are covered to help you find an object in a photo. You will see how a complex object such as a face can be recognized by a browser as you move toward the end of the book. Finally, you will focus on algorithms to create a human interface.

By the end of this book, you will be familiarized with the application of complex Computer Vision algorithms to develop your own applications, without spending much time learning sophisticated theory.

Style and approach

This book is an easy-to-follow project-based guide that throws you directly into the excitement of the Computer Vision theme. A "more in less" approach is followed by important concepts explained in a to-the-point, easy-to-understand manner.

Computer Vision for the Web

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Table of Contents

Computer Vision for the Web

Credits

About the Author

About the Reviewer

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Why subscribe?

Free access for Packt account holders

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

1. Math Never Was So Simple!

Installation and core structure representation of JSFeat

Initializing the project

Understanding a digital image

Loading an image into a matrix

Basic matrix operations

Going deeper

Matrix displaying

Useful functions and where to use them

Sorting using JSFeat

Linear algebra

A perspective example

Summary

2. Turn Your Browser into Photoshop

Introducing the tracking.js library

Installation and image loading

Conversion between JSFeat and tracking.js image formats

What is filtering and how to use it?

Image convolution

The Gaussian filter and separate convolution

The box blur

The integral image

Basic edge detection

The Sobel filter

Other operators

Advanced image processing

The Canny edge detector

Histogram equalization

Summary

3. Easy Object Detection for Everyone

Detecting color objects

Using predefined colors with the tracking.js library

Using your own colors

Digging into the tracking.js API

Using the <img> and <video> tags

Building a custom tracker

Image features

Detecting key points

A practical example

Descriptors and object matching

The BRIEF and ORB descriptors

Descriptors implementation and their matching

Finding an object location

Summary

4. Smile and Wave, Your Face Has Been Tracked!

Face detection with JSFeat

Face detection using Haar-like features

Brightness binary features

Tagging people with tracking.js

Haar features with tracking.js

Tagging people in photos

Head tracking with Camshift

The idea behind head tracking

The head tracking application

Summary

5. May JS Be with You! Control Your Browser with Motion

Basic tracking with tracking.js

An example of an object tracking application

Controlling objects with the head motion

The Head-coupled perspective

Controlling a simple box

Optical flow for motion estimation

The Lucas-Kanade optical flow

Optical flow map with oflow

Track points with JSFeat

Zooming with gestures

Summary

6. What's Next?

Refresh your memory

Importance of client-side scripting

Other interesting libraries in Computer Vision

CCV library and its extensions

Face detection and more

Object detection with js-objectdetect

Summary

Index

Computer Vision for the Web

Copyright © 2015 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: October 2015

Production reference: 1091015

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78588-617-1

www.packtpub.com

Credits

Author

Foat Akhmadeev

Reviewer

Noritsuna Imamura

Acquisition Editor

Tushar Gupta

Content Development Editor

Amey Varangaonkar

Technical Editor

Vivek Pala

Copy Editor

Pranjali Chury

Project Coordinator

Francina Pinto

Proofreader

Safis Editing

Indexer

Mariammal Chettiyar

Graphics

Disha Haria

Production Coordinator

Arvindkumar Gupta

Cover Work

Arvindkumar Gupta

About the Author

Foat Akhmadeev has 5 years of experience in software development and research. He completed his master's degree in the year 2014 from the Kazan Federal University, Russia. He has worked on different projects, including development of high-loaded websites written in Java and real-time object detection for mobile phones. He has an extensive background in the field of Computer Vision. He has also written a scientific paper on 3D reconstruction from a single image. For more information, you can visit his website at http://foat.me.

About the Reviewer

Noritsuna Imamura is a specialist in embedded Linux/Android-based Computer Vision, and is one of the main members of SIProp.org (http://siprop.org/). His main works are as follows:

• ITRI Smart Glass, which is similar to Google Glass. He worked on this using Android 4.3 and OpenCV 2.4 in June 2014 (https://www.itri.org.tw/chi/Content/techTransfer/tech_tran_cont.aspx?&SiteID=1&MmmID=620622510147005345&Keyword=&MSid=4858).
• The Treasure Hunting Robot, a brainwave controlling robot that he developed in February 2012 (http://www.siprop.org/en/2.0/index.php?product%2FTreasureHuntingRobot).
• OpenCV for Android NDK. This has been included since Android 4.0.1 (http://tools.oesf.biz/android-4.0.1_r1.0/search?q=SIProp).
• The Auto Chasing Turtle, a human face recognition robot with Kinect, which he developed in February 2011 (http://www.siprop.org/ja/2.0/index.php?product%2FAutoChasingTurtle).
• Feel Sketch—an AR Authoring Tool and AR Browser as an Android application, which he developed in December 2009 (http://code.google.com/p/feelsketch/).

He can be contacted via e-mail at <[email protected]>.

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