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Proceedings Paper

Cognitive-based fusion using information sets for moving target recognition
Author(s): Erik P. Blasch; Scott N. J. Watamaniuk; Peter Svenmarck
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Paper Abstract

Leveraging human fusion can enhance computational moving target recognition algorithms. Cognitive models exploit a human's visual discrimination of object color, size, motion, and orientation. From the biological pathways of the magnocellular and parvocellular pathways, information sets are fused for a single perception of an object. For instance, a human tracking a target could take advantage of a moving target relative to stationary objects or a large object amongst smaller objects. Cognition, or attention to salient information, can be explicitly represented as a set of information outside a covariance boundary. The paper proposes a cognitive-based attentional model that leverages information asymmetries for moving target recognition.

Paper Details

Date Published: 4 August 2000
PDF: 10 pages
Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); doi: 10.1117/12.395071
Show Author Affiliations
Erik P. Blasch, Wright State Univ. (United States)
Scott N. J. Watamaniuk, Wright State Univ. (United States)
Peter Svenmarck, Linkoeping Univ. (Sweden)

Published in SPIE Proceedings Vol. 4052:
Signal Processing, Sensor Fusion, and Target Recognition IX
Ivan Kadar, Editor(s)

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