A Biologically Inspired Connectionist Architecture for Directing Attention to Salient Visual Field Objects

David Lee Enke

doi:10.1109/ICSMC.1997.638078

A Biologically Inspired Connectionist Architecture for Directing Attention to Salient Visual Field Objects

David Lee Enke

Engineering Management and Systems Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

In an attempt to incorporate basic visual attention abilities into existing artificial vision systems, a neural model of the bidirectional interactions within and between the brain regions believed to be involved in human visual attention has been developed. This model currently gives an artificial vision system the ability to attend to salient, or pop-out features and objects within the vision system''s field of view. After a review of the physiology of human visual attention, a network model of the aforementioned neural interactions is presented, followed by a demonstration of its performance.

Original language	American English
Journal	Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics, 1997
DOIs	https://doi.org/10.1109/ICSMC.1997.638078
State	Published - Jan 1 1997

Keywords

Attention
Bidirectional Interactions
Computer Vision
Machine Vision
Neural Model
Neural Net Architecture
Physiological Models
Salient Visual Field Objects

Disciplines

Operations Research, Systems Engineering and Industrial Engineering

Access to Document

10.1109/ICSMC.1997.638078License: Unspecified

A Biologically Inspired Connectionist Architecture for DirectingFinal published version, 694 KBLicense: Unspecified

Cite this

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title = "A Biologically Inspired Connectionist Architecture for Directing Attention to Salient Visual Field Objects",

abstract = " In an attempt to incorporate basic visual attention abilities into existing artificial vision systems, a neural model of the bidirectional interactions within and between the brain regions believed to be involved in human visual attention has been developed. This model currently gives an artificial vision system the ability to attend to salient, or pop-out features and objects within the vision system''s field of view. After a review of the physiology of human visual attention, a network model of the aforementioned neural interactions is presented, followed by a demonstration of its performance.",

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AB - In an attempt to incorporate basic visual attention abilities into existing artificial vision systems, a neural model of the bidirectional interactions within and between the brain regions believed to be involved in human visual attention has been developed. This model currently gives an artificial vision system the ability to attend to salient, or pop-out features and objects within the vision system''s field of view. After a review of the physiology of human visual attention, a network model of the aforementioned neural interactions is presented, followed by a demonstration of its performance.

KW - Attention

KW - Bidirectional Interactions

KW - Computer Vision

KW - Machine Vision

KW - Neural Model

KW - Neural Net Architecture

KW - Physiological Models

KW - Salient Visual Field Objects

UR - https://scholarsmine.mst.edu/engman_syseng_facwork/198

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M3 - Article

JO - Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics, 1997

JF - Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics, 1997

ER -

A Biologically Inspired Connectionist Architecture for Directing Attention to Salient Visual Field Objects

Abstract

Keywords

Disciplines

Access to Document

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