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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
Author Profile Icon Eugene Khvedchenia
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

Estimating the camera motion from a pair of images

Before we set out to actually find the motion between two cameras, let's examine the inputs and the tools we have at hand to perform this operation. First, we have two images of the same scene from (hopefully not extremely) different positions in space. This is a powerful asset, and we will make sure that we use it. As for tools, we should take a look at mathematical objects that impose constraints over our images, cameras, and the scene.

Two very useful mathematical objects are the fundamental matrix (denoted by F) and the essential matrix (denoted by E), which impose a constraint over corresponding 2D points in two images of the scene. They are mostly similar, except that the essential matrix is assuming usage of calibrated cameras; this is the case for us, so we will choose it. OpenCV allows us to find the fundamental matrix via the findFundamentalMat function...

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