Automatic acquisition of context models and its application to video surveillance

Oliver Brdiczka*, Pong Chi YUEN, Sofia Zaidenberg, Patrick Reignier, James L. Crowley

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

22 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 languageEnglish
Title of host publicationProceedings - 18th International Conference on Pattern Recognition, ICPR 2006
Pages1175-1178
Number of pages4
DOIs
Publication statusPublished - 2006
Event18th International Conference on Pattern Recognition, ICPR 2006 - Hong Kong, China
Duration: 20 Aug 200624 Aug 2006

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume1
ISSN (Print)1051-4651

Conference

Conference18th International Conference on Pattern Recognition, ICPR 2006
Country/TerritoryChina
CityHong Kong
Period20/08/0624/08/06

Scopus Subject Areas

  • Computer Vision and Pattern Recognition

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