A Dynamic Hierarchical Clustering Method for Trajectory-Based Unusual Video Event Detection

被引：87

作者：

Jiang, Fan ^{[1
]}

Wu, Ying ^{[1
]}

Katsaggelos, Aggelos K. ^{[1
]}

机构：

[1] Northwestern Univ, Dept Elect Engn & Comp Sci, Evanston, IL 60208 USA

来源：

IEEE TRANSACTIONS ON IMAGE PROCESSING | 2009年 / 18卷 / 04期

关键词：

Event detection; unsupervised clustering; video surveillance; RECOGNITION;

D O I：

10.1109/TIP.2008.2012070

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：907 / 913

页数：7

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