Beschreibung

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.
Contents Introduction; Part I. The Background: Proj

Inhaltsangabe

From the contents: Introduction
Part I. The Background: Projective Geometry, Transformations and Estimation:
1. Outline of Part I
2. Projective geometry and transformations of 2D
3. Projective geometry and transformations of 3D
4. Estimation - 2D projective transforms; Part II. Camera Geometry and Single View Geometry:
5. Outline of Part II
6. Camera models
7. Camera calibration
8. More single view geometry; Part III. Two View Geometry:
9. Outline of Part III
10. Epipolar geometry and the fundamental matrix
11. 3D reconstruction and structure computations
12. Computation of F
13. Structure computation
14. The case of planes
15. Affine epipolar geometry; Part IV. Three View Geometry:
16. Outline of Part IV
17. The trifocal tensor
18. Computation of T; Part V. N View Geometry:
19. Outline of Part V
20. N-linearities
21. Computation of the quadrifocal tensor
22. N-view computational methods
23. Chirality
24. D egenerate configurations
25. Auto-calibration
26. Image rectification; Appendix 1. Useful formulas; Appendix 2. Tensor notation; Appendix 3. Gaussian (normal) and chi-squared distributions; Appendix 4. Numerical algorithms; Bibliography; Index

Klappentext

A basic problem in computer vision is to understand the structure of a real world scene. This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. Richard Hartley and Andrew Zisserman provide comprehensive background material and explain how to apply the methods and implement the algorithms. First Edition HB (2000): 0-521-62304-9