Paper
4 August 2000 Cognitive-based fusion using information sets for moving target recognition
Erik P. Blasch, Scott N. J. Watamaniuk, Peter Svenmarck
Author Affiliations +
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Erik P. Blasch, Scott N. J. Watamaniuk, and 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); https://doi.org/10.1117/12.395071
Lens.org Logo
CITATIONS
Cited by 3 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Target recognition

Motion models

Cognitive modeling

Visualization

Information fusion

Target detection

Visual process modeling

RELATED CONTENT

Feature extraction inspired by V1 in visual cortex
Proceedings of SPIE (April 10 2018)
Computational models of shape saliency
Proceedings of SPIE (March 15 2019)
Neural network modeling of visual recognition
Proceedings of SPIE (July 01 1992)
Scanpath memory binding: multiple read-out experiments
Proceedings of SPIE (May 19 1999)

Back to Top