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Analyzing vision at the complexity level

Analyzing vision at the complexity level <jats:title>Abstract</jats:title><jats:p>The general problem of visual search can be shown to be computationally intractable in a formal, complexity-theoretic sense, yet visual search is extensively involved in everyday perception, and biological systems manage to perform it remarkably well. Complexity level analysis may resolve this contradiction. Visual search can be reshaped into tractability through approximations and by optimizing the resources devoted to visual processing. Architectural constraints can be derived using the minimum cost principle to rule out a large class of potential solutions. The evidence speaks strongly against bottom-up approaches to vision. In particular, the constraints suggest an attentional mechanism that exploits knowledge of the specific problem being solved. This analysis of visual search performance in terms of attentional influences on visual information processing and complexity satisfaction allows a large body of neurophysiological and psychological evidence to be tied together.</jats:p> http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Behavioral and Brain Sciences CrossRef

Analyzing vision at the complexity level

Behavioral and Brain Sciences , Volume 13 (3): 423-445 – Sep 1, 1990

Analyzing vision at the complexity level


Abstract

<jats:title>Abstract</jats:title><jats:p>The general problem of visual search can be shown to be computationally intractable in a formal, complexity-theoretic sense, yet visual search is extensively involved in everyday perception, and biological systems manage to perform it remarkably well. Complexity level analysis may resolve this contradiction. Visual search can be reshaped into tractability through approximations and by optimizing the resources devoted to visual processing. Architectural constraints can be derived using the minimum cost principle to rule out a large class of potential solutions. The evidence speaks strongly against bottom-up approaches to vision. In particular, the constraints suggest an attentional mechanism that exploits knowledge of the specific problem being solved. This analysis of visual search performance in terms of attentional influences on visual information processing and complexity satisfaction allows a large body of neurophysiological and psychological evidence to be tied together.</jats:p>

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Publisher
CrossRef
ISSN
0140-525X
DOI
10.1017/s0140525x00079577
Publisher site
See Article on Publisher Site

Abstract

<jats:title>Abstract</jats:title><jats:p>The general problem of visual search can be shown to be computationally intractable in a formal, complexity-theoretic sense, yet visual search is extensively involved in everyday perception, and biological systems manage to perform it remarkably well. Complexity level analysis may resolve this contradiction. Visual search can be reshaped into tractability through approximations and by optimizing the resources devoted to visual processing. Architectural constraints can be derived using the minimum cost principle to rule out a large class of potential solutions. The evidence speaks strongly against bottom-up approaches to vision. In particular, the constraints suggest an attentional mechanism that exploits knowledge of the specific problem being solved. This analysis of visual search performance in terms of attentional influences on visual information processing and complexity satisfaction allows a large body of neurophysiological and psychological evidence to be tied together.</jats:p>

Journal

Behavioral and Brain SciencesCrossRef

Published: Sep 1, 1990

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