000			02195nam a22003498i 4500
001			CR9780511811685
003			UkCbUP
005			20200124160256.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			101021s2003||||enk o ||1 0|eng|d
020			_a9780511811685 (ebook)
020			_z9780521540513 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aTA1634 _b.H38 2003
082	0	0	_a006.3/7 _222
100	1		_aHartley, Richard, _eauthor.
245	1	0	_aMultiple view geometry in computer vision / _cRichard Hartley, Andrew Zisserman.
250			_aSecond edition.
264		1	_aCambridge : _bCambridge University Press, _c2003.
300			_a1 online resource (xvi, 655 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
520			_aA 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.
650		0	_aComputer vision.
650		0	_aGeometry, Projective.
700	1		_aZisserman, Andrew, _eauthor.
776	0	8	_iPrint version: _z9780521540513
856	4	0	_uhttps://doi.org/10.1017/CBO9780511811685
999			_c519973 _d519971