Tracking With a Hierarchical Partitioned Particle Filter and Movement Modelling

Zsolt L. Husz, Andrew M. Wallace, Patrick R. Green

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

We present an approach to track human subjects using an articulated human framework. First, we describe the articulated hierarchical human model. Second, we develop a stochastic hierarchical, partitioned, particle filter based on the natural structure and limb dependency of the human body. We apply this to track human subjects in video sequences using likelihoods adapted to the hierarchical process. Finally, we evaluate the effectiveness of the described approach using publicly available datasets.

Original languageEnglish
Pages (from-to)1571-1584
Number of pages14
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume41
Issue number6
DOIs
Publication statusPublished - Dec 2011

Keywords

  • Hierarchical partitioned particle filter
  • movement
  • tracking
  • video analytics
  • windowed-mean

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