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Singular value decomposition based particle filter for tracking in complex environment

  • Yan Huang*
  • , Xiling Luo
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Tracking in complex environment is an important and challenging problem. Most of the existing methods adopt low level features derived from objects appearance. In contrast to this mainstream approach, this paper introduces a new method considering image as matrix then employing singular value as the features. For evaluating the likelihood between template and the candidate, which is weight update in particle filter, we offer Bhattacharyya coefficient based metrics. We compare our proposed algorithm with typical color histogram based particle filter in two challenges: confusing color in background and illumination change. Experiment results show that our approach achieves better tracking accuracy and robustness.

Original languageEnglish
Title of host publicationProceedings of the 12th IASTED International Conference on Intelligent Systems and Control, ISC 2009
Pages75-81
Number of pages7
StatePublished - 2009
Event12th IASTED International Conference on Intelligent Systems and Control, ISC 2009 - Cambridge, MA, United States
Duration: 2 Nov 20094 Nov 2009

Publication series

NameProceedings of the IASTED International Conference on Intelligent Systems and Control
ISSN (Print)1025-8973

Conference

Conference12th IASTED International Conference on Intelligent Systems and Control, ISC 2009
Country/TerritoryUnited States
CityCambridge, MA
Period2/11/094/11/09

Keywords

  • Bhattacharyya coefficient
  • Particle filter
  • Singular value decomposition

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