A Context Space Model for Detecting Anomalous Behaviour in Video Surveillance

Wiliem, Arnold, Madasu, Vamsi, Boles, Wageeh W., & Yarlagadda, Prasad K. (2012) A Context Space Model for Detecting Anomalous Behaviour in Video Surveillance. In International Conference on Information Technology 2012 (ICIT12), 16-18 April 2012, Las Vegas, Nevada, USA.

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Having a good automatic anomalous human behaviour detection is one of the goals of smart surveillance systems’ domain of research. The automatic detection addresses several human factor issues underlying the existing surveillance systems. To create such a detection system, contextual information needs to be considered. This is because context is required in order to correctly understand human behaviour. Unfortunately, the use of contextual information is still limited in the automatic anomalous human behaviour detection approaches. This paper proposes a context space model which has two benefits: (a) It provides guidelines for the system designers to select information which can be used to describe context; (b)It enables a system to distinguish between different contexts. A comparative analysis is conducted between a context-based system which employs the proposed context space model and a system which is implemented based on one of the existing approaches. The comparison is applied on a scenario constructed using video clips from CAVIAR dataset. The results show that the context-based system outperforms the other system. This is because the context space model allows the system to considering knowledge learned from the relevant context only.

Impact and interest:

4 citations in Scopus
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ID Code: 50027
Item Type: Conference Paper
Refereed: Yes
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MECHANICAL ENGINEERING (091300)
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012
Deposited On: 02 May 2012 22:56
Last Modified: 30 Jun 2017 14:43

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