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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

Reconstructing a 3D scene from calibrated cameras


We saw in the previous recipe that it is possible to recover the position of a camera observing a 3D scene, when this one is calibrated. The approach described took advantage of the fact that, sometimes, the coordinates of some 3D points visible in the scene might be known. We will now learn that if a scene is observed from more than one point of view, 3D pose and structure can be reconstructed even if no information about the 3D scene is available. This time, we will use correspondences between image points in the different views in order to infer 3D information. We will introduce a new mathematical entity encompassing the relation between two views of a calibrated camera, and we will discuss the principle of triangulation in order to reconstruct 3D points from 2D images.

How to do it...

Let's again use the camera we calibrated in the first recipe of this chapter and take two pictures of some scene. We can match feature points between these...

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