Multiple view geometry in computer vision
 Responsibility
 Richard Hartley, Andrew Zisserman.
 Edition
 2nd ed.
 Imprint
 Cambridge, U.K. ; New York : Cambridge University Press, 2003.
 Physical description
 655 p. : ill. (some col.) ; 25 cm.
At the library
Engineering Library (Terman)
Stacks
Call number  Status 

TA1634 .H38 2003  Unknown 
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Description
Creators/Contributors
 Author/Creator
 Hartley, Richard.
 Contributor
 Zisserman, Andrew.
Contents/Summary
 Bibliography
 Includes bibliographical references (p. 634645) and index.
 Contents

 1. Introduction  a tour of multiple view geometry Part 0. The Background: Projective Geometry, Transformations and Estimation: 2. Projective geometry and transformations of 2D 3. Projective geometry and transformations of 3D 4. Estimation  2D projective transforms 5. Algorithm evaluation and error analysis Part I. Camera Geometry and Single View Geometry: 6. Camera models 7. Computation of the camera matrix 8. More single view geometry Part II. TwoView Geometry: 9. Epipolar geometry and the fundamental matrix 10. 3D reconstruction of cameras and structure 11. Computation of the fundamental matrix F 12. Structure computation 13. Scene planes and homographies 14. Affine epipolar geometry Part III. ThreeView Geometry: 15. The trifocal tensor 16. Computation of the trifocal tensor T Part IV. N View Geometry: 17. Nlinearities and multiple view tensors 18. Nview computational methods 19. Autocalibration 20. Duality 21. Chirality 22. Degenerate configurations Part V. Appendices: Appendix 1. Tensor notation Appendix 2. Gaussian (normal) and chisquared distributions Appendix 3. Parameter estimation. Appendix 4. Matrix properties and decompositions Appendix 5. Leastsquares minimization Appendix 6. Iterative Estimation Methods Appendix 7. Some special plane projective transformations Bibliography Index.
 (source: Nielsen Book Data)9780521540513 20160528
 Publisher's Summary
 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.
(source: Nielsen Book Data)9780521540513 20160528
Subjects
Bibliographic information
 Publication date
 2003
 ISBN
 0521540518
 9780521540513