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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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Toc

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 the fundamental matrix of an image pair


The previous recipe showed you how to recover the projective equation of a single camera. In this recipe, we will explore the projective relationship that exists between two images that display the same scene. These two images could have been obtained by moving a camera at two different locations to take pictures from two viewpoints or by using two cameras, each of them taking a different picture of the scene. When these two cameras are separated by a rigid baseline, we use the term stereovision.

Getting ready

Let's now consider two cameras observing a given scene point, as shown in the following figure:

We learned that we can find the image x of a 3D point X by tracing a line joining this 3D point with the camera's center. Conversely, the scene point that has its image at the position x on the image plane can be located anywhere on this line in the 3D space. This implies that if we want to find the corresponding point of a given image point...

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