A dynamic hierarchical clustering method for trajectory-based unusual video event detection

Fan Jiang*, Ying Wu, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalArticle

82 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)907-913
Number of pages7
JournalIEEE Transactions on Image Processing
Volume18
Issue number4
DOIs
StatePublished - Mar 10 2009

Keywords

  • Event detection
  • Unsupervised clustering
  • Video surveillance

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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