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OpenCV 3 Computer Vision Application Programming Cookbook

You're reading from   OpenCV 3 Computer Vision Application Programming Cookbook Recipes to make your applications see

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Product type Paperback
Published in Feb 2017
Publisher
ISBN-13 9781786469717
Length 474 pages
Edition 3rd Edition
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Author (1):
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Robert Laganiere Robert Laganiere
Author Profile Icon Robert Laganiere
Robert Laganiere
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Table of Contents (15) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating Pixels 3. Processing the Colors of an Image 4. Counting the Pixels with Histograms 5. Transforming Images with Morphological Operations 6. Filtering the Images 7. Extracting Lines, Contours, and Components 8. Detecting Interest Points 9. Describing and Matching Interest Points 10. Estimating Projective Relations in Images 11. Reconstructing 3D Scenes 12. Processing Video Sequences 13. Tracking Visual Motion 14. Learning from Examples

Recognizing faces using nearest neighbors of local binary patterns

Our first exploration of machine learning techniques will start with what is probably the simplest approach, namely nearest neighbor classification. We will also present the local binary pattern feature, a popular representation encoding the textural patterns and contours of an image in a contrast independent way.

Our illustrative example will concern the face recognition problem. This is a very challenging problem that has been the object of numerous researches over the past 20 years. The basic solution we present here is one of the face recognition methods implemented in OpenCV. You will quickly realize that this solution is not very robust and works only under very favorable conditions. Nevertheless, this approach constitutes an excellent introduction to machine learning and to the face recognition problem.

How to do it...

The OpenCV library proposes a number of face recognition methods implemented as a subclass of the generic...

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