Multiple View Geometry in Computer Vision Second Edition

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Richard HartleyCambridge University PressEdition: 2, 3/25/2004EAN 9780521540513, ISBN10: 0521540518Paperback, 672 pages, 24.8 x 17.5 x 3.6 cmLanguage: EnglishA basic problem in com puter 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.1. Introduction - a tour of multiple view geometryPart 0. The BackgroundProjective Geometry, Transformations and Estimation2. Projective geometry and transformations of 2D3. Projective geometry and transformations of 3D4. Estimation - 2D projective transforms5. Algorithm evaluation and error analysisPart I. Camera Geometry and Single View Geometry6. Camera models7. Computation of the camera matrix8. More single view geometryPart II. Two-View Geometry9. Epipolar geometry and the fundamental matrix10. 3D reconstruction of cameras and structure11. Computation of the fundamental matrix F12. Structure computation13. Scene planes and homographies14. Affine epipolar geometryPart III. Three-View Geometry15. The trifocal tensor16. Computation of the trifocal tensor TPart IV. N -View Geometry17. N-linearities and multiple view tensors18. N-view computational methods19. Auto-calibration20. Duality21. Chirality22. Degenerate configurationsPart V. Appendices Appendix 1. Tensor notationAppendix 2. Gaussian (normal) and chi-squared distributionsAppendix 3. Parameter estimation. Appendix 4. Matrix properties and decompositionsAppendix 5. Least-squares minimizationAppendix 6. Iterative Estimation MethodsAppendix 7. Some special plane projective transformationsBibliographyIndex.'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 Show more