Adversarial behavior recognition from layered and persistent sensing systems

Georgiy Levchuk; Olga Mendoza-Schrock; Wayne Shebilske

doi:10.1117/12.818676

29 April 2009 Adversarial behavior recognition from layered and persistent sensing systems

Georgiy Levchuk, Olga Mendoza-Schrock, Wayne Shebilske

Proceedings Volume 7347, Evolutionary and Bio-Inspired Computation: Theory and Applications III; 73470W (2009) https://doi.org/10.1117/12.818676
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

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.

Citation Download Citation

Georgiy Levchuk, Olga Mendoza-Schrock, and Wayne Shebilske "Adversarial behavior recognition from layered and persistent sensing systems", Proc. SPIE 7347, Evolutionary and Bio-Inspired Computation: Theory and Applications III, 73470W (29 April 2009); https://doi.org/10.1117/12.818676

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