DocumentCode :
1186317
Title :
A Dynamic Hierarchical Clustering Method for Trajectory-Based Unusual Video Event Detection
Author :
Jiang, Fan ; Wu, Ying ; Katsaggelos, Aggelos K.
Author_Institution :
Electr. Eng. & Comput. Sci. Dept., Northwestern Univ., Evanston, IL
Volume :
18
Issue :
4
fYear :
2009
fDate :
4/1/2009 12:00:00 AM
Firstpage :
907
Lastpage :
913
Abstract :
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.
Keywords :
hidden Markov models; object detection; pattern clustering; video signal processing; 2-depth greedy search strategy; dynamic hierarchical clustering method; hidden Markov models; object trajectories; trajectory-based unusual video event detection; unsupervised clustering; Event detection; unsupervised clustering; video surveillance;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2008.2012070
Filename :
4798178
Link To Document :
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