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

Post on 30-Dec-2015

21 views 0 download

description

A Dynamic Hierarchical Clustering Method for Trajectory-Based Unusual Video Event Detection. Fan Jiang, Ying Wu , Senior Member, IEEE, and Aggelos K. Katsaggelos , Fellow, IEEE IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 18, NO. 4, APRIL 2009. Introduction. Hidden Markov Model (HMM). - PowerPoint PPT Presentation

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

Fan Jiang, Ying Wu, Senior Member, IEEE, and

Aggelos K. Katsaggelos, Fellow, IEEEIEEE TRANSACTIONS ON IMAGE

PROCESSING, VOL. 18, NO. 4, APRIL 2009

IntroductionHidden Markov Model (HMM)

Cross Likelihood Ratio (CLR)X = training trajectoryY = likelihood trajectoryλx, λy = HMM of X or Y

Bayesian Information Criterion (BIC)

Dissimilarity

TRAJECTORY CLUSTERINGDynamic hierarchical clustering (DHC)

Fifteen categories of any three trajectory groups according to different nearest neighbors

Merging can be rejected (exclusion) if

Substituting BIC

Where :

Assume :

Sufficient condition to be satisfied

2-depth greedy search algorithm

NORMAL CLUSTER IDENTIFICATION ANDABNORMALITY DETECTION

If

then trajectory i is unusual

Examples of normal (a)–(d) and unusual (e)–(h) trajectories.

Thank You