4 August 2000 Cognitive-based fusion using information sets for moving target recognition
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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.
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Erik P. Blasch, Erik P. Blasch, Scott N. J. Watamaniuk, Scott N. J. Watamaniuk, Peter Svenmarck, Peter Svenmarck, "Cognitive-based fusion using information sets for moving target recognition", Proc. SPIE 4052, Signal Processing, Sensor Fusion, and Target Recognition IX, (4 August 2000); doi: 10.1117/12.395071; https://doi.org/10.1117/12.395071
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