• 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