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OpenCV Computer Vision with Java

You're reading from   OpenCV Computer Vision with Java Create multiplatform computer vision desktop and web applications using the combination of OpenCV and Java

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Product type Paperback
Published in Jul 2015
Publisher
ISBN-13 9781783283972
Length 174 pages
Edition 1st Edition
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Author (1):
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Daniel Lelis Baggio Daniel Lelis Baggio
Author Profile Icon Daniel Lelis Baggio
Daniel Lelis Baggio
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Table of Contents (9) Chapters Close

Preface 1. Setting Up OpenCV for Java FREE CHAPTER 2. Handling Matrices, Files, Cameras, and GUIs 3. Image Filters and Morphological Operators 4. Image Transforms 5. Object Detection Using Ada Boost and Haar Cascades 6. Detecting Foreground and Background Regions and Depth with a Kinect Device 7. OpenCV on the Server Side Index

Chapter 5. Object Detection Using Ada Boost and Haar Cascades

This chapter shows a very interesting feature of OpenCV—detecting faces in an image or a video stream. In the latter case, we call it face tracking. In order to do so, this chapter dives into machine-learning algorithms, specifically supervised learning with boosting. We will cover the Viola-Jones classifier and its theory as well as the details on how to use the face-trained classifiers that are bundled with OpenCV.

In this chapter, we will be covering the following topics:

  • The boosting theory
  • Viola-Jones classifier
  • Detecting faces
  • Learning new objects

By the end of this chapter, you will be able to understand the theory behind face classifiers through boosting, and the Viola-Jones classifier. You will also know how to use straightforward face classifiers. Besides, you will be able to create your own object classifier for different objects.

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