Multiple View Geometry in Computer Vision

by Richard Hartley , Andrew Zisserman

• ISBN13: 9780521540513
• ISBN10: 0521540518
• eBook ISBN(s): 9781139636124
• Additional ISBN(s): 9780521574716
• Edition: 2nd
• Format: Paperback
• Copyright: 2004-04-19
• Publisher: Cambridge University Press
• More Book Details
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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.

Table of 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. Two-View 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. Three-View Geometry: 15. The trifocal tensor

16. Computation of the trifocal tensor T

Part IV. N -View Geometry: 17. N-linearities and multiple view tensors

18. N-view computational methods

19. Auto-calibration

20. Duality

21. Chirality

22. Degenerate configurations

Part V. Appendices: Appendix 1. Tensor notation

Appendix 2. Gaussian (normal) and chi-squared distributions

Appendix 3. Parameter estimation. Appendix 4. Matrix properties and decompositions

Appendix 5. Least-squares minimization

Appendix 6. Iterative Estimation Methods

Appendix 7. Some special plane projective transformations

Bibliography

Index.