Online anomaly detection in videos by clustering dynamic exemplars

We propose a non-parametric hierarchical event model to perform online anomaly detection in videos. A dynamic exemplar set is first used to represent observed event samples which updates itself every time when a new sample comes in. Upon this set, clusters are extracted to summarize the exemplars, o...

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Bibliographische Detailangaben

Hauptverfasser:	Jie Feng, Chao Zhang, Pengwei Hao
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Anomaly detection clustering Computational modeling Computer vision Conferences hierarchical model Legged locomotion Pattern recognition Surveillance Videos
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