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Mastering OpenCV with Practical Computer Vision Projects

You're reading from   Mastering OpenCV with Practical Computer Vision Projects This is the definitive advanced tutorial for OpenCV, designed for those with basic C++ skills. The computer vision projects are divided into easily assimilated chapters with an emphasis on practical involvement for an easier learning curve.

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Product type Paperback
Published in Dec 2012
Publisher Packt
ISBN-13 9781849517829
Length 340 pages
Edition 1st Edition
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Table of Contents (15) Chapters Close

Mastering OpenCV with Practical Computer Vision Projects
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Cartoonifier and Skin Changer for Android FREE CHAPTER 2. Marker-based Augmented Reality on iPhone or iPad 3. Marker-less Augmented Reality 4. Exploring Structure from Motion Using OpenCV 5. Number Plate Recognition Using SVM and Neural Networks 6. Non-rigid Face Tracking 7. 3D Head Pose Estimation Using AAM and POSIT 8. Face Recognition using Eigenfaces or Fisherfaces Index

Reconstruction from many views


Now that we know how to recover the motion and scene geometry from two cameras, it would seem trivial to get the parameters of additional cameras and more scene points simply by applying the same process. This matter is in fact not so simple as we can only get a reconstruction that is up-to-scale, and each pair of pictures gives us a different scale.

There are a number of ways to correctly reconstruct the 3D scene data from multiple views. One way is of resection or camera pose estimation, also known as Perspective N-Point(PNP), where we try to solve for the position of a new camera using the scene points we have already found. Another way is to triangulate more points and see how they fit into our existing scene geometry; this will tell us the position of the new camera by means of the Iterative Closest Point(ICP) procedure. In this chapter we will discuss using OpenCV's solvePnP functions to achieve the first method.

The first step we choose in this kind of...

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