Comparison of Bayesian and empirical ranking approaches to visual perception

被引:28
作者
Howe, Catherine Q.
Lotto, R. Beau
Purves, Dale [1 ]
机构
[1] Duke Univ, Ctr Cognit Neurosci, Durham, NC 27708 USA
[2] Duke Univ, Dept Neurobiol, Durham, NC 27708 USA
[3] UCL, Inst Ophthalmol, London W13, England
关键词
vision; perception; Bayesian decision theory; empirical ranking theory;
D O I
10.1016/j.jtbi.2006.01.017
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Much current vision research is predicated on the idea-and a rapidly growing body of evidence-that. visual percepts are generated according to the empirical significance of light stimuli rather than their physical characteristics. As a result, an increasing number of investigators have asked how visual perception can be rationalized in these terms. Here, we compare two different theoretical frameworks for predicting what observers actually see in response to visual stimuli: Bayesian decision theory and empirical ranking theory. Deciding which of these approaches has greater merit is likely to determine how the statistical operations that apparently underlie visual perception are eventually understood. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:866 / 875
页数:10
相关论文
共 34 条
[1]  
[Anonymous], 2005, Perceiving Geometry: Geometrical Illusions Explained by Natural Scene Statistics
[2]  
Bayes T., 1763, Philosophical Transactions, V53, P370, DOI [10.1098/rstl.1763.0053, DOI 10.1098/RSTL.1763.0053]
[3]  
Berkeley G., 1709, NEW THEORY VISION
[4]   SHAPE FROM TEXTURE - IDEAL OBSERVERS AND HUMAN PSYCHOPHYSICS [J].
BLAKE, A ;
BULTHOFF, HH ;
SHEINBERG, D .
VISION RESEARCH, 1993, 33 (12) :1723-1737
[5]   Bayesian color constancy [J].
Brainard, DH ;
Freeman, WT .
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION, 1997, 14 (07) :1393-1411
[6]   Bayesian contour integration [J].
Feldman, J .
PERCEPTION & PSYCHOPHYSICS, 2001, 63 (07) :1171-1182
[7]   THE GENERIC VIEWPOINT ASSUMPTION IN A FRAMEWORK FOR VISUAL-PERCEPTION [J].
FREEMAN, WT .
NATURE, 1994, 368 (6471) :542-545
[8]   Edge co-occurrence in natural images predicts contour grouping performance [J].
Geisler, WS ;
Perry, JS ;
Super, BJ ;
Gallogly, DP .
VISION RESEARCH, 2001, 41 (06) :711-724
[9]   Illusions, perception and Bayes [J].
Geisler, WS ;
Kersten, D .
NATURE NEUROSCIENCE, 2002, 5 (06) :508-510
[10]   STOCHASTIC RELAXATION, GIBBS DISTRIBUTIONS, AND THE BAYESIAN RESTORATION OF IMAGES [J].
GEMAN, S ;
GEMAN, D .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1984, 6 (06) :721-741