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PRL
2006

On-line trajectory clustering for anomalous events detection

10 years 1 months ago
On-line trajectory clustering for anomalous events detection
In this paper we propose a trajectory clustering algorithm suited for video surveillance systems. Trajectories are clustered on-line, as the data are collected, and clusters are organised in a tree-like structure that, augmented with probability information, can be used to perform behaviour analysis, since it allows the identification of anomalous events. Key words: trajectory clustering, on-line clustering, behaviour analysis
Claudio Piciarelli, Gian Luca Foresti
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where PRL
Authors Claudio Piciarelli, Gian Luca Foresti
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