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Robust Mean Shift Tracking with Background Information

  • Zhao Liu
  • Guiyu Feng
  • Dewen Hu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7368)

Abstract

The background-weighted histogram (BWH) has been proposed in mean shift tracking algorithm to reduce the interference of background in target localization. However, the BWH also reduces the weight for part of complex object. Mean shift with BWH model is unable to track object with scale change. In this paper, we integrate an object/background likelihood model into the mean shift tracking algorithm. Experiments on both synthetic and real world video sequences demonstrate that the proposed method could effectively estimate the scale and orientation changes of the target. The proposed method can still robustly track the object when the target is not well initialized.

Keywords

Object tracking Mean shift Gaussian mixture model Background information 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Zhao Liu
    • 1
  • Guiyu Feng
    • 2
  • Dewen Hu
    • 1
  1. 1.Department of Automatic Control, College of Mechatronics and AutomationNational University of Defense TechnologyChangshaChina
  2. 2.Institute of Computing TechnologyBeijing Jiaotong UniversityBeijingChina

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