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OpenCV Computer Vision Application Programming Cookbook Second Edition

You're reading from   OpenCV Computer Vision Application Programming Cookbook Second Edition Over 50 recipes to help you build computer vision applications in C++ using the OpenCV library

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Product type Paperback
Published in Aug 2014
Publisher Packt
ISBN-13 9781782161486
Length 374 pages
Edition 1st 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 (13) Chapters Close

Preface 1. Playing with Images FREE CHAPTER 2. Manipulating Pixels 3. Processing Color Images with Classes 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. Processing Video Sequences Index

Computing a homography between two images


The second recipe of this chapter showed you how to compute the fundamental matrix of an image pair from a set of matches. In projective geometry, another very useful mathematical entity also exists. This one can be computed from multiview imagery and, as we will see, is a matrix with special properties.

Getting ready

Again, let's consider the projective relation between a 3D point and its image on a camera, which we introduced in the first recipe of this chapter. Basically, we learned that this equation relates a 3D point with its image using the intrinsic properties of the camera and the position of this camera (specified with a rotation and a translation component). If we now carefully examine this equation, we realize that there are two special situations of particular interest. The first situation is when two views of a scene are separated by a pure rotation. It can then be observed that the fourth column of the extrinsic matrix will be made up...

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