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Computer Vision for the Web

Computer Vision for the Web

By : Akhmadeev
3.3 (4)
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Computer Vision for the Web

Computer Vision for the Web

3.3 (4)
By: Akhmadeev

Overview of this book

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.
Table of Contents (8 chapters)
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Chapter 2. Turn Your Browser into Photoshop

It is likely that you have used Photoshop or at least heard about it. With a few clicks, you can easily modify an image, enhance it, or do some sort of preprocessing. Actually, it is not that hard to do using JavaScript. For most of the functions, you need only a couple lines of code. This chapter is mostly about filters and image segmentation. Here, we will discuss many popular techniques and their applications. Moreover, we will introduce a new JavaScript library—tracking.js (http://trackingjs.com). It is mostly used for object tracking applications, but there are many utilties, which are relevant to the topic. It is interesting to know how to use both JSFeat, which we introduced in the first chapter, and tracking.js libraries together. We will see how to do this. Besides, we will compare their advantages in terms of image filtering. We will start from the installation of the new library and then follow the filter examples from...

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Computer Vision for the Web
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