1.

Record Nr.

UNINA9910965469303321

Autore

Hartley Richard

Titolo

Multiple view geometry in computer vision / / Richard Hartley, Andrew Zisserman

Pubbl/distr/stampa

Cambridge, UK ; ; New York, : Cambridge University Press, 2003

ISBN

9786610458127

9781107141698

1107141699

9781139636124

113963612X

9781280458125

1280458127

9780511184512

0511184514

9780511185359

0511185359

9780511187117

0511187114

9780511313332

0511313330

9780511811685

0511811683

9780511186189

0511186185

Edizione

[2nd ed.]

Descrizione fisica

1 online resource (xvi, 655 pages) : digital, PDF file(s)

Altri autori (Persone)

ZissermanAndrew

Disciplina

006.3/7

Soggetti

Computer vision

Geometry, Projective

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

Nota di bibliografia

Includes bibliographical references (p. 634-645) and index.

Nota di contenuto

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.

Sommario/riassunto

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.