A Dynamic Hierarchical Clustering Method for Trajectory-Based Unusual Video Event Detection

The proposed unusual video event detection method is based on unsupervised clustering of object trajectories, which are modeled by hidden Markov models (HMM). The novelty of the method includes a dynamic hierarchical process incorporated in the trajectory clustering algorithm to prevent model overfi...

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Veröffentlicht in:IEEE transactions on image processing 2009-04, Vol.18 (4), p.907-913
Hauptverfasser: Fan Jiang, Ying Wu, Katsaggelos, A.K.
Format: Artikel
Sprache:eng
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Zusammenfassung:The proposed unusual video event detection method is based on unsupervised clustering of object trajectories, which are modeled by hidden Markov models (HMM). The novelty of the method includes a dynamic hierarchical process incorporated in the trajectory clustering algorithm to prevent model overfitting and a 2-depth greedy search strategy for efficient clustering.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2008.2012070