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Automatic Acquisition of Context Models and its Application to Video Surveillance

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5 Author(s)

This paper addresses the problem of automatically acquiring context models from data. Context and human behavior are represented using a state model, called situation model. This model consists of different layers referring to entities, filters, roles, relations, situation and situation relationship. We propose a framework for the automatic acquisition of these different layers. In particular, this paper proposes a novel generic situation acquisition algorithm. The algorithm is also successfully applied to a video surveillance task and is evaluated by the public CAVIAR video database. The results are encouraging

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Pattern Recognition, 2006. ICPR 2006. 18th International Conference on  (Volume:1 )

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