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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

Cascade classifier detection and training

One might be wondering how OpenCV could detect faces as this would be a very straightforward task for a couple-of-month old baby, and it looks quite complicated to tell a computer how to accomplish it. We will divide the problem in two parts—object detection, which is applying a classifier and retrieving the object position when the classifier says so, and training a new classifier to learn new objects that should be mostly rigid.

OpenCV Cascade Classifier initially implemented a face-detection technique known as the Viola-Jones detector, first developed by Paul Viola and Michael Jones, which uses the so-called Haar-like features, named after Alfréd Haar wavelets. These features are based on thresholds of sums and differences of rectangular regions of raw image values. Later, this classifier also enabled the use of Local Binary Patterns (LBP) features, which are integer values in contrast to Haar-like features; this results in faster...

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