Welcome to Journal of University of Chinese Academy of Sciences,Today is

›› 2013, Vol. 30 ›› Issue (2): 244-250.DOI: 10.7523/j.issn.1002-1175.2013.02.016

Previous Articles     Next Articles

MUGG-based modeling of trajectories and anomaly detection

GUI Shu1,2, GUO Li1, LU Hai-Xian1, XIE Jin-Sheng1   

  1. 1. College of Information Science and Technology, University of Science and Technology of China, Hefei 230022, China;
    2. Electronic Engineering Institute, Hefei 230037, China
  • Received:2012-01-19 Revised:2012-03-08 Online:2013-03-15

Abstract:

A probabilistic model named MUGG (mixture of unilateral generalized Gaussians) is designed for modeling the distribution of trajectories in visual scene. Information of trajectory is calculated to determine whether the trajectory is abnormal. This method is unsupervised and independent of prior knowledge.It is fit for time-varying environment with the real-time updated model. Its availability and robustness shown by experiments proves the application value.

Key words: anomaly detection, MUGG, trajectory learning, trajectory distance

CLC Number: