Detecting and discriminating behavioural anomalies

12 years 7 months ago
Detecting and discriminating behavioural anomalies
This paper aims to address the problem of anomaly detection and discrimination in complex behaviours, where anomalies are subtle and difficult to detect owing to the complex temporal dynamics and correlations among multiple objects’ behaviours. Specifically, we decompose a complex behaviour pattern according to its temporal characteristics or spatial-temporal visual contexts. The decomposed behaviour is then modelled using a cascade of Dynamic Bayesian Networks (CasDBNs). In contrast to existing standalone models, the proposed behaviour decomposition and cascade modelling offers distinct advantage in simplicity for complex behaviour modelling. Importantly, the decomposition and cascade structure map naturally to the structure of complex behaviour, allowing for a more effective detection of subtle anomalies in surveillance videos. Comparative experiments using both indoor and outdoor data are carried out to demonstrate that, in addition to the novel capability of discriminating di...
Chen Change Loy, Tao Xiang, Shaogang Gong
Added 17 Sep 2011
Updated 17 Sep 2011
Type Journal
Year 2011
Where PR
Authors Chen Change Loy, Tao Xiang, Shaogang Gong
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