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Proceedings Paper

Adversarial behavior recognition from layered and persistent sensing systems
Author(s): Georgiy Levchuk; Olga Mendoza-Schrock; Wayne Shebilske
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Paper Abstract

Advances in multi-sensor automated target recognition, tracking, and Wide Area Persistent Surveillance promise to enable a broad spectrum of intent and behavior recognition models. However, a significant gap remains between coordinated behavior analyses tools working at high information abstraction and target identification and tracking systems working with direct inputs from motion imagery. In this paper, we describe the problem of modeling adversarial behavior signatures faced by Air Force researchers, present a range of solutions to automate the discovery of behavior patterns, and outline the gap in the research space to enable efficient integration of multi-level information exploitation, analyses and sensor management tools.

Paper Details

Date Published: 29 April 2009
PDF: 17 pages
Proc. SPIE 7347, Evolutionary and Bio-Inspired Computation: Theory and Applications III, 73470W (29 April 2009); doi: 10.1117/12.818676
Show Author Affiliations
Georgiy Levchuk, Aptima Inc. (United States)
Olga Mendoza-Schrock, Air Force Research Lab. (United States)
Wayne Shebilske, Wright State Univ. (United States)

Published in SPIE Proceedings Vol. 7347:
Evolutionary and Bio-Inspired Computation: Theory and Applications III
Teresa H. O'Donnell; Misty Blowers; Kevin L. Priddy, Editor(s)

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