中国邮电高校学报(英文) ›› 2009, Vol. 16 ›› Issue (2): 117-121.doi: 10.1016/S1005-8885(08)60215-0

• Image recognization • 上一篇    下一篇

Tracking people through partial occlusions

卢建国,蔡安妮   

  1. School of Telecommunication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-04-30
  • 通讯作者: 卢建国

Tracking people through partial occlusions

LU Jian-guo, CAI An-ni   

  1. School of Telecommunication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-04-30
  • Contact: LU Jian-guo

摘要:

This article presents a novel people-tracking approach to cope with partial occlusions caused by scene objects. Instead of predicting when and where the occlusions will occur, a part-based model is used to model the pixel distribution of the target body under occlusion. The subdivided patches corresponding to a template image will be tracked independently using Markov chain Monte Carlo (MCMC) method. A set of voting-based rules is established for the patch-tracking result to verify if the target is indeed located at the estimated position. Experiments show the effectiveness of the proposed method.

关键词:

;partial;occlusion,;part-based;model,;MCMC,;voting-based;rules

Abstract:

This article presents a novel people-tracking approach to cope with partial occlusions caused by scene objects. Instead of predicting when and where the occlusions will occur, a part-based model is used to model the pixel distribution of the target body under occlusion. The subdivided patches corresponding to a template image will be tracked independently using Markov chain Monte Carlo (MCMC) method. A set of voting-based rules is established for the patch-tracking result to verify if the target is indeed located at the estimated position. Experiments show the effectiveness of the proposed method.

Key words:

partial occlusion;part-based model;MCMC;voting-based rules