Detection of unusual trajectories using multi-objective evolutionary algorithms and rough sets

Tomasz G. Smolinski; Trevor Newell; Samantha McDaniel; David Pokrajac

doi:10.1117/12.2024580

30 September 2013 Detection of unusual trajectories using multi-objective evolutionary algorithms and rough sets

Tomasz G. Smolinski, Trevor Newell, Samantha McDaniel, David Pokrajac

Proceedings Volume 8857, Signal and Data Processing of Small Targets 2013; 88570F (2013) https://doi.org/10.1117/12.2024580
Event: SPIE Optical Engineering + Applications, 2013, San Diego, California, United States

Abstract

Detection of unusual trajectories of moving objects (e.g., people, automobiles, etc.) is an important problem in many civilian and military surveillance applications. In this work, we propose a multi-objective evolutionary algorithms and rough sets-based approach that breaks down 2-dimensional trajectories into a set of additive components, which then can be used to build a classifier capable of recognizing typical, but yet unseen trajectories, and identifying those that seem suspicious.

Citation Download Citation

Tomasz G. Smolinski, Trevor Newell, Samantha McDaniel, and David Pokrajac "Detection of unusual trajectories using multi-objective evolutionary algorithms and rough sets", Proc. SPIE 8857, Signal and Data Processing of Small Targets 2013, 88570F (30 September 2013); https://doi.org/10.1117/12.2024580

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