4 August 2000 Cognitive-based fusion using information sets for moving target recognition
Author Affiliations +
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, 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


Effects of using a 3D model on the performance of...
Proceedings of SPIE (May 21 2015)
Progress in building a cognitive vision system
Proceedings of SPIE (August 02 2016)
Scanpath memory binding: multiple read-out experiments
Proceedings of SPIE (May 18 1999)
Human vision model for advanced autonomous seekers
Proceedings of SPIE (August 23 1999)

Back to Top