Multiple View Geometry in Computer Vision

by Richard Hartley, Andrew Zisserman

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.

Genres: Computer Science, Engineering, Reference, Science, Programming, Mathematics, Textbooks

672 pages, Kindle Edition

First published July 31, 2000

Reviews

[Wooi Hen Yap]

The book title says it all. It's not exaggerating when I considered this one a must have for students, practitioners and researchers alike intended to work on 3D computer vision. It covers broad yet deep state-of-the-art methods in 3D reconstruction from multiple cameras, from single camera. However it is not for the faint-hearted .. Not recommended for beginners who had no good knowledge linear algebra, bayesian estimation or tensor algebra.

[Jiri]

I can now officially say I see in 3D.

[Álvaro Francesc]

The Bible of 3D Vision

[Delhi Irc]

Location: GG6 IRC
Accession no: DL026989