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Object-based visual attention for computer vision

delete2003-05-01
delete251
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OA
AI
Y
Yaoru Sun
R
Robert B. Fisher
DOI:10.1016/S0004-3702(02)00399-5delete
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Abstract

Abstract

En 中文
In this paper. a novel model of object-based visual attention extending Duncan's Integrated Competition Hypothesis [Phil. Trans. R. Soc. London B 353 (1998) 1307-1317] is presented. In contrast to the attention mechanisms used in most previous machine vision systems which drive attention based on the spatial location hypothesis, the mechanisms which direct visual attention in our system are object-driven as well as feature-driven. The competition to gain visual attention occurs not only within an object but also between objects. For this purpose, two new mechanisms in the proposed model are described and analyzed in detail. The first mechanism computes the visual salience of objects and groupings; the second one implements the hierarchical selectivity of attentional shifts. The results of the new approach on synthetic and natural images are reported. (C) 2003 Elsevier Science B.V. All rights reserved.
Keywords:
visual attention
object-based visual attention
integrated competition
grouping salience
hierarchical selectivity
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Journal

Artificial Intelligence Review cover
Artificial Intelligence Review
IF:
13.9
Papers:
6.1K
Citations:
1.9W

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