Variance reduction techniques in particle-based visual contour tracking

Daniel Ponsa, Antonio M. López

Research output: Contribution to journalArticleResearchpeer-review

9 Citations (Scopus)

Abstract

This paper presents a comparative study of three different strategies to improve the performance of particle filters, in the context of visual contour tracking: the unscented particle filter, the Rao-Blackwellized particle filter, and the partitioned sampling technique. The tracking problem analyzed is the joint estimation of the global and local transformation of the outline of a given target, represented following the active shape model approach. The main contributions of the paper are the novel adaptations of the considered techniques on this generic problem, and the quantitative assessment of their performance in extensive experimental work done. © 2009 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)2372-2391
JournalPattern Recognition
Volume42
DOIs
Publication statusPublished - 1 Nov 2009

Keywords

  • Active shape models
  • Contour tracking
  • Importance sampling
  • Kalman filter
  • Particle filter
  • Partitioned sampling
  • Rao-Blackwellization
  • Unscented particle filter

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