Path: utzoo!utgpu!jarvis.csri.toronto.edu!mailrus!wuarchive!udel!princeton!phoenix!harnad
From: harnad@phoenix.Princeton.EDU (S. R. Harnad)
Newsgroups: comp.ai
Subject: Visual Search & Complexity: BBS Call for Commentators
Keywords: computer vision, complexity theory, perception, neurophysiology
Message-ID: <10491@phoenix.Princeton.EDU>
Date: 19 Sep 89 05:40:16 GMT
Organization: Princeton University, NJ
Lines: 41



Below is the abstract of a forthcoming target article to appear in
Behavioral and Brain Sciences (BBS), an international,
interdisciplinary journal that provides Open Peer Commentary on important
and controversial current research in the biobehavioral and cognitive
sciences. Commentators must be current BBS Associates or nominated by a 
current BBS Associate. To be considered as a commentator on this article,
to suggest other appropriate commentators, or for information about how
to become a BBS Associate, please send email to:
	 harnad@princeton.edu              or write to:
BBS, 20 Nassau Street, #240, Princeton NJ 08542  [tel: 609-921-7771]
____________________________________________________________________

Analyzing Vision at the Complexity Level

John K. Tsotsos

Department of Computer Science,
University of Toronto and
The Canadian Institute for Advanced Research

The general problem of visual search can be shown to be computationally
intractable in a formal complexity-theoretic sense, yet visual search
is widely 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 purely bottom-up approaches
to vision. This analysis of visual search performance in terms of
task-directed influences on visual information processing and
complexity satisfaction allows a large body of neurophysiological and
psychological evidence to be tied together.

-- 
Stevan Harnad  INTERNET:  harnad@confidence.princeton.edu   harnad@princeton.edu
srh@flash.bellcore.com      harnad@elbereth.rutgers.edu    harnad@princeton.uucp
CSNET:    harnad%confidence.princeton.edu@relay.cs.net
BITNET:   harnad1@umass.bitnet      harnad@pucc.bitnet            (609)-921-7771