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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
Languages
Tools
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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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Toc

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

Tracing feature points in a video

We learned in previous chapters that analyzing an image through some of its most distinctive points can lead to effective and efficient computer vision algorithms. This is also true for image sequences in which the motion of some interest points can be used to understand how the different elements of a captured scene move. In this recipe, you will learn how to perform a temporal analysis of a sequence by tracking feature points as they move from frame to frame.

How to do it...

To start the tracking process, the first thing to do is to detect the feature points in an initial frame. You then try to track these points in the next frame. Obviously, since we are dealing with a video sequence, there is a good chance that the object, on which the feature points are found, has moved (this motion can also be due to camera movement). Therefore, you must search around a point's previous location in order to find its new location in the next frame. This is what...

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