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 organized 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. (c) 2006 Elsevier B.V. All rights reserved.
On-line trajectory clustering for anomalous events detection
PICIARELLI, Claudio;FORESTI, Gian Luca
2006-01-01
Abstract
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 organized 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. (c) 2006 Elsevier B.V. All rights reserved.File in questo prodotto:
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