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