Multiple View Geometry in Computer Vision [Hardcover]

Richard Hartley (Author), Andrew Zisserman (Author)

Book Description

Publication Date: July 31, 2000 | ISBN-10: 0521623049 | ISBN-13: 978-0521623049

A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques used in the book for solving this are taken from projective geometry and photogrammetry. 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. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. The authors provide comprehensive background material, so a reader familiar with linear algebra and basic numerical methods will be able to understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.

Editorial Reviews

Review

"The authors have succeeded very well in describing the main techniques in mainstream multiple view geometry, both classical and modern, in a clear and consistent way....I heartily recommend this book." Computing Reviews --This text refers to the Paperback edition.

Book Description

Recent developments in the theory and practice of scene reconstruction are described in detail in a unified framework. The distinctive flavour is that the approach is uncalibrated. Geometric principles and their algebraic representation are covered, enabling readers to understand the projective geometry and estimation algorithms presented, and implement them directly.

Product Details

• Hardcover: 624 pages
• Publisher: Cambridge University Press (July 31, 2000)
• Language: English
• ISBN-10: 0521623049
• ISBN-13: 978-0521623049
• Product Dimensions: 10 x 7.2 x 1.4 inches
• Shipping Weight: 3.4 pounds
• Average Customer Review: 4.0 out of 5 stars  See all reviews (11 customer reviews)
• Amazon Best Sellers Rank: #2,780,325 in Books (See Top 100 in Books)
  • #48 in Books > Computers & Technology > Computer Science > Artificial Intelligence > Computer Vision

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Customer Reviews

Most Helpful Customer Reviews

11 of 11 people found the following review helpful:

4.0 out of 5 stars Good on the explanations of the theory, April 25, 2009

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calvinnme - See all my reviews
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This review is from: Multiple View Geometry in Computer Vision (Paperback)

This book is very complete and rigorous in its explanations of the theory. However, I just think I like the approach in An Invitation to 3-D Vision a bit better. This book is better illustrated than that one and is more careful in its explanations, but this book just seems more focused on providing complete proofs than giving you a feel for how you would approach a real problem. Even the exercises are more along the lines of proofs. I like how An Invitation to 3-D Vision ends the book with a complete example. In all fairness, though, this book does have quite a bit of Matlab code on its website.

The book begins with some background material on 2D and 3D geometry. Then the author explains single-view geometry and how cameras map an image in 3D space to an image. Two-view geometry is next, with the author describing the epipolar geometry of two cameras ahd projective reconstruction from resulting image map correspondences. Part three of the book extends ideas to three cameras and the resulting trifocal geometry. The final section of the book takes the algorithms of the book to N views. Thus this book has a simple and straightforward structure that belies the complexity of the material.

If you are really researching this subject you should probably have this book for explanation, illustrations, and rigor, and the Invitation book for enlightenment through a good example-based approach. You should also have Introductory Techniques for 3-D Computer Vision as a text on the individual pieces of algorithms involved in 3D vision. And don't even think about getting into this subject unless you already have a firm foundation in linear algebra, image processing, and computer vision in general as found in Computer Vision, which is my favorite introductory computer vision text.

13 of 15 people found the following review helpful:

5.0 out of 5 stars A must for readers in computer vision, January 10, 2001

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"wktang" (Hong Kong) - See all my reviews

This review is from: Multiple View Geometry in Computer Vision (Hardcover)

It is the best book in this area that I have seen up to now. It is well-organized and all the notations and words are friendly to beginners and even experts in this field. Included materials are really tracing the latest advanced techniques. Actually, it is great that there are a lot of exercises at the ends of each chapters but there is no sufficient solutions or detail explanations to each questions.

10 of 11 people found the following review helpful:

4.0 out of 5 stars Comment on the first edition, January 3, 2004

By A Customer

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This review is from: Multiple View Geometry in Computer Vision (Paperback)

The first edition of this book could have been much better written. It took up a lot of topics, but treated each in a summary fashion. In fairness, though, I must say that this may be as good as any other book with its aim and scope, and better than some. Any writer on computer vision faces the problem of guessing who the reader is likely to be and what the reader's background is. Also, each of the various topics really merits a sizable book. In particular, the mathematics needs a truly mathematical treatment in a separate book. I have not seen this second edition, but there was room for improvement over the first edition.