From Features to Perceptual Categories

First we review an analysis of conditions that should be met if features are to provide robust inferences about world properties. Features meeting these conditions provide indices into especially useful categories of visual properties. Then we show that for a given set of elemental concepts the categories associated with these properties have a natural hierarchical (specialization) structure. We argue that this structure provides constraints on the form and type of categories that are inferred when visual objects are classified.

[1]  Azriel Rosenfeld,et al.  Human and Machine Vision , 1983 .

[2]  Thomas O. Binford,et al.  Inferring Surfaces from Images , 1981, Artif. Intell..

[3]  David G. Lowe,et al.  Perceptual Organization and Visual Recognition , 2012 .

[4]  A. Witkin,et al.  On the Role of Structure in Vision , 1983 .

[5]  Roger J. Watt,et al.  Pattern Recognition by Man and Machine , 1991 .

[6]  D. Marr.  A theory for cerebral neocortex , 1970, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[7]  David Marr,et al.  VISION A Computational Investigation into the Human Representation and Processing of Visual Information , 2009 .

[8]  Jacob Feldman,et al.  Constructing perceptual categories , 1992, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  D'arcy W. Thompson.  On Growth and Form , 1945 .

[10]  Zenon W. Pylyshyn,et al.  Computational processes in human vision : an interdisciplinary perspective , 1988 .