Premium
Intermediate Vision: Architecture, Implementation, and Use
Author(s) -
Chapman David
Publication year - 1992
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1207/s15516709cog1604_3
Subject(s) - computer science , visual search , task (project management) , visual processing , architecture , set (abstract data type) , artificial intelligence , massively parallel , parallel processing , image processing , computer vision , image (mathematics) , computer hardware , parallel computing , perception , psychology , programming language , neuroscience , engineering , art , systems engineering , visual arts
This article describes an implemented architecture for intermediate vision. By integrating a variety of Intermediate visual mechanisms and putting them to use in support of concrete activity, the implementation demonstrates their utility. The sytem, SIVS, models psychophysical discoveries about visual attention and search. It is designed to be efficiently implementable in slow, massively parallel, locally connected hardware, such as that of the brain. SIVS addresses five fundamental problems. Visual attention is required to restrict processing to task‐relevant locations in the image. Visual search finds such locations. Visual routines are a means for nonuniform processing based on task demands. Intermediate objects keep track of intermediate results of this processing. Visual operators are a set of relatively abstract, general‐purpose primitives for spatial analysis, out of which visual routines are assembled.