30 September 2013 Detection of unusual trajectories using multi-objective evolutionary algorithms and rough sets
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Proceedings Volume 8857, Signal and Data Processing of Small Targets 2013; 88570F (2013); doi: 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.
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Tomasz G. Smolinski, Trevor Newell, Samantha McDaniel, 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); doi: 10.1117/12.2024580; http://dx.doi.org/10.1117/12.2024580
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KEYWORDS
Evolutionary algorithms

RGB color model

Optimization (mathematics)

Databases

Reconstruction algorithms

Signal processing

Video

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