Automatic Acquisition of Context Models and its Application to Video Surveillance

Oliver Brdiczka 1 Pong Chi Yuen Sofia Zaidenberg 1 Patrick Reignier 1 James L. Crowley 1
1 PRIMA - Perception, recognition and integration for observation of activity
Inria Grenoble - Rhône-Alpes, UJF - Université Joseph Fourier - Grenoble 1, INPG - Institut National Polytechnique de Grenoble , CNRS - Centre National de la Recherche Scientifique : UMR5217
Abstract : 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
keyword : Bridges Context modeling Databases Feedback Filtering Filters Humans Sensor systems Testing image representation surveillance video signal processing CAVIAR video database automatic context model acquisition context representation data context model human behavior representation situation acquisition algorithm situation model state model video surveillance
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Conference papers
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https://hal.inria.fr/hal-00788082
Contributor : Sofia Zaidenberg <>
Submitted on : Wednesday, February 13, 2013 - 4:44:17 PM
Last modification on : Tuesday, November 27, 2018 - 8:46:01 PM

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Oliver Brdiczka, Pong Chi Yuen, Sofia Zaidenberg, Patrick Reignier, James L. Crowley. Automatic Acquisition of Context Models and its Application to Video Surveillance. 18th International Conference on Pattern Recognition, ICPR 2006., Yuan Yan Tang and Patrick Wang and G. Lorette and Daniel So Yeung, Aug 2006, Hong Kong, Hong Kong SAR China. pp.1175-1178, ⟨10.1109/ICPR.2006.292⟩. ⟨hal-00788082⟩

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