Multiple View Geometry in Computer Vision

Author:   Richard Hartley (Australian National University, Canberra) ,  Andrew Zisserman (University of Oxford)
Publisher:   Cambridge University Press
Edition:   2nd Revised edition
ISBN:  

9780511811685


Publication Date:   25 January 2011
Format:   Undefined
Availability:   Available To Order   Availability explained
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Multiple View Geometry in Computer Vision


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Author:   Richard Hartley (Australian National University, Canberra) ,  Andrew Zisserman (University of Oxford)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press (Virtual Publishing)
Edition:   2nd Revised edition
ISBN:  

9780511811685


ISBN 10:   0511811683
Publication Date:   25 January 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Undefined
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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Reviews

'I am very positive about this book. 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.' Computing Reviews '... a book which is timely, extremely thorough and commendably clear ... Overall, the approach is masterly ... The authors have managed to present the very essence of the subject in a way which the most subtle ideas seem natural and straightforward. I have never seen such a clear exploration of the geometry of vision. I would wholeheartedly recommend this book. It deserves to be in the library of every serious researcher in the field of computer vision.' Journal of Robotica 'The new edition features an extended introduction covering the key ideas in the book (which itself have 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.' Zentralblatt MATH


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