000			03081nam a22003618i 4500
001			CR9780511984037
003			UkCbUP
005			20200124160317.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			101124s1996||||enk o ||1 0|eng|d
020			_a9780511984037 (ebook)
020			_z9780521461092 (hardback)
020			_z9780521064996 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aBF311 _b.P3534 1996
082	0	0	_a153.7 _220
245	0	0	_aPerception as Bayesian inference / _cedited by David C. Knill, Whitman Richards.
264		1	_aCambridge : _bCambridge University Press, _c1996.
300			_a1 online resource (xi, 516 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).
505	0		_aIntroduction / D.C. Knill, D. Kersten and A. Yuille -- 1. Pattern theory: A unifying perspective / D. Mumford -- 2. Modal structure and reliable inference / A. Jepson, W. Richards and D.C. Knill -- 3. Priors, preferences and categorical percepts / W. Richards, A. Jepson and J. Feldman -- 4. Bayesian decision theory and psychophysics / A.L. Yuille and H.H. Bulthoff -- 5. Observer theory, Bayes theory, and psychophysics / B.M. Bennett, D.D. Hoffman, C. Prakash and S.N. Richman -- 6. Implications of a Bayesian formulation of visual information for processing for psychophysics / D.C. Knill, D. Kersten and P. Mamassian -- 7. Shape from texture: Ideal observers and human psychophysics / A. Blake, H.H. Bulthoff and D. Sheinberg -- 8. A computational theory for binocular stereopsis / P.N. Belhumeur -- 9. The generic viewpoint assumption in a Bayesian framework / W.T. Freeman -- 10. Experiencing and perceiving visual surfaces / K. Nakayama and S. Shimojo.
520			_aBayesian probability theory has emerged not only as a powerful tool for building computational theories of vision, but also as a general paradigm for studying human visual perception. This 1996 book provides an introduction to and critical analysis of the Bayesian paradigm. Leading researchers in computer vision and experimental vision science describe general theoretical frameworks for modelling vision, detailed applications to specific problems and implications for experimental studies of human perception. The book provides a dialogue between different perspectives both within chapters, which draw on insights from experimental and computational work, and between chapters, through commentaries written by the contributors on each others' work. Students and researchers in cognitive and visual science will find much to interest them in this thought-provoking collection.
650		0	_aPerception _xCongresses.
650		0	_aBayesian statistical decision theory _xCongresses.
700	1		_aKnill, David C., _eeditor.
700	1		_aRichards, Whitman, _eeditor.
776	0	8	_iPrint version: _z9780521461092
856	4	0	_uhttps://doi.org/10.1017/CBO9780511984037
999			_c521604 _d521602