A dynamic hierarchical clustering method for trajectory-based unusual video event detection. Fan Jiang, Ying Wu, Katsaggelos, A. K A., Jiang, F., Wu, Y., & Katsaggelos, A. K A. IEEE Transactions on Image Processing, 18(4):907–913, IEEE, apr, 2009. ![A dynamic hierarchical clustering method for trajectory-based unusual video event detection [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex 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. © 2009 IEEE.
@article{jiang2009dynamic,
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. {\textcopyright} 2009 IEEE.},
author = {{Fan Jiang} and {Ying Wu} and Katsaggelos, Aggelos K A.K. and Jiang, Fan and Wu, Ying and Katsaggelos, Aggelos K A.K.},
doi = {10.1109/TIP.2008.2012070},
issn = {1057-7149},
journal = {IEEE Transactions on Image Processing},
keywords = {Event detection,Unsupervised clustering,Video surveillance},
month = {apr},
number = {4},
pages = {907--913},
publisher = {IEEE},
title = {{A dynamic hierarchical clustering method for trajectory-based unusual video event detection}},
url = {http://ieeexplore.ieee.org/document/4798178/},
volume = {18},
year = {2009}
}
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