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Mastering OpenCV 3

You're reading from   Mastering OpenCV 3 Get hands-on with practical Computer Vision using OpenCV 3

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Product type Paperback
Published in Apr 2017
Publisher
ISBN-13 9781786467171
Length 250 pages
Edition 2nd Edition
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Authors (6):
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Shervin Emami Shervin Emami
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Shervin Emami
David Millán Escrivá David Millán Escrivá
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David Millán Escrivá
Eugene Khvedchenia Eugene Khvedchenia
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Eugene Khvedchenia
Daniel Lelis Baggio Daniel Lelis Baggio
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Daniel Lelis Baggio
Roy Shilkrot Roy Shilkrot
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Roy Shilkrot
Jason Saragih Jason Saragih
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Jason Saragih
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Toc

Reconstruction from many views


Now that we know how to recover the motion and scene geometry from two cameras, it would seem simple 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 upto scale, and each pair of pictures has a different scale.

There are a number of ways to correctly reconstruct the 3D scene data from multiple views. One way to achieve camera pose estimation or camera resectioning, is the Perspective N-Point(PnP) algorithm, where we try to solve for the position of a new camera using N 3D scene points, which we have already found and their respective 2D image points. 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 point cloud registration. In this section, we will discuss using OpenCV's solvePnP functions that implements the first method...

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