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.
Original language | English |
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Title of host publication | Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006 |
Pages | 1175-1178 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 2006 |
Event | 18th International Conference on Pattern Recognition, ICPR 2006 - , Hong Kong Duration: 20 Aug 2006 → 24 Aug 2006 https://ieeexplore.ieee.org/xpl/conhome/11159/proceeding |
Publication series
Name | Proceedings - International Conference on Pattern Recognition |
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Volume | 1 |
ISSN (Print) | 1051-4651 |
Conference
Conference | 18th International Conference on Pattern Recognition, ICPR 2006 |
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Country/Territory | Hong Kong |
Period | 20/08/06 → 24/08/06 |
Internet address |
Scopus Subject Areas
- Computer Vision and Pattern Recognition