Multiple View Geometry in Computer Vision

Nonfiction, Computers, Application Software, Computer Graphics, General Computing, Science & Nature, Technology
Cover of the book Multiple View Geometry in Computer Vision by Richard Hartley, Andrew Zisserman, Cambridge University Press
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Author: Richard Hartley, Andrew Zisserman ISBN: 9781139636124
Publisher: Cambridge University Press Publication: March 25, 2004
Imprint: Cambridge University Press Language: English
Author: Richard Hartley, Andrew Zisserman
ISBN: 9781139636124
Publisher: Cambridge University Press
Publication: March 25, 2004
Imprint: Cambridge University Press
Language: English

A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.

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A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.

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