Automatic acquisition of context models and its application to video surveillance

Oliver Brdiczka; Pong C. Yuen; Sofia Zaidenberg; Patrick Reignier; James L. Crowley

doi:10.1109/ICPR.2006.292

Automatic acquisition of context models and its application to video surveillance

Oliver Brdiczka^*, Pong C. Yuen, Sofia Zaidenberg, Patrick Reignier, James L. Crowley

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

23 Citations (Scopus)

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
Title of host publication	Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006
Pages	1175-1178
Number of pages	4
DOIs	https://doi.org/10.1109/ICPR.2006.292
Publication status	Published - 2006
Event	18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China Duration: 20 Aug 2006 → 24 Aug 2006

Publication series

Name	Proceedings - International Conference on Pattern Recognition
Volume	1
ISSN (Print)	1051-4651

Conference

Conference	18th International Conference on Pattern Recognition, ICPR 2006
Country/Territory	China
City	Hong Kong
Period	20/08/06 → 24/08/06

Scopus Subject Areas

Computer Vision and Pattern Recognition

Access to Document

10.1109/ICPR.2006.292

Cite this

Brdiczka, O., Yuen, P. C., Zaidenberg, S., Reignier, P., & Crowley, J. L. (2006). Automatic acquisition of context models and its application to video surveillance. In Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006 (pp. 1175-1178). Article 1699099 (Proceedings - International Conference on Pattern Recognition; Vol. 1). https://doi.org/10.1109/ICPR.2006.292

@inproceedings{69b246da6fbd4449978d64815758f66c,

title = "Automatic acquisition of context models and its application to video surveillance",

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.",

author = "Oliver Brdiczka and Yuen, {Pong C.} and Sofia Zaidenberg and Patrick Reignier and Crowley, {James L.}",

year = "2006",

doi = "10.1109/ICPR.2006.292",

language = "English",

isbn = "0769525210",

series = "Proceedings - International Conference on Pattern Recognition",

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booktitle = "Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006",

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Brdiczka, O, Yuen, PC, Zaidenberg, S, Reignier, P & Crowley, JL 2006, Automatic acquisition of context models and its application to video surveillance. in Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006., 1699099, Proceedings - International Conference on Pattern Recognition, vol. 1, pp. 1175-1178, 18th International Conference on Pattern Recognition, ICPR 2006, Hong Kong, China, 20/08/06. https://doi.org/10.1109/ICPR.2006.292

Automatic acquisition of context models and its application to video surveillance. / Brdiczka, Oliver; Yuen, Pong C.; Zaidenberg, Sofia et al.
Proceedings - 18th International Conference on Pattern Recognition, ICPR 2006. 2006. p. 1175-1178 1699099 (Proceedings - International Conference on Pattern Recognition; Vol. 1).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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AU - Crowley, James L.

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AB - 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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Automatic acquisition of context models and its application to video surveillance

Abstract

Publication series

Conference

Scopus Subject Areas

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