Segment Model Based Vehicle Motion Analysis

  • Authors:
  • Pengfei Zhu;Weiming Hu;Xi Li;Li Li

  • Affiliations:
  • -;-;-;-

  • Venue:
  • AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
  • Year:
  • 2009

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Abstract

Motion analysis is a very attractive research direction in computer vision field. In this paper, we propose a framework for analyzing real vehicle motion in visual traffic surveillance by using Segment Model (SM), which is a kind of probabilistic model. SM can grasp the underlying information of observation sequence by using segment distribution. It has been proved to be more precise than that of HMM. In the experiments, we compare our approach with the template matching method based on the Hausdorff distance and the state space method based on the Hidden Markov Model (HMM). The experimental results show the effectiveness of our approach.