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Multiple View Geometry in Computer Vision
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Table of 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: 6. 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. Degenerate 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.

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How to reconstruct scenes from images using geometry and algebra, with applications to computer vision.

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