Rao-blackwellized particle filter for human appearance and position tracking

Jesus Martinez-del-Rincon, Carlos Orrite-Urunuela, Gregory Rogez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In human motion analysis, the joint estimation of appearance, body pose and location parameters is not always tractable due to its huge computational cost. In this paper, we propose a Rao-Blackwellized Particle Filter for addressing the problem of human pose estimation and tracking. The advantage of the proposed approach is that Rao-Blackwellization allows the state variables to be splitted into two sets, being one of them analytically calculated from the posterior probability of the remaining ones. This procedure reduces the dimensionality of the Particle Filter, thus requiring fewer particles to achieve a similar tracking performance. In this manner, location and size over the image are obtained stochastically using colour and motion clues, whereas body pose is solved analytically applying learned human Point Distribution Models.

Original languageEnglish
Title of host publicationPattern Recognition and Image Analysis, Pt 1, Proceedings
EditorsJ Marti, JM Benedi, AM Mendonca, J Serrat
Place of PublicationBERLIN
PublisherSpringer
Pages201-208
Number of pages8
Volume4477 LNCS
EditionPART 1
ISBN (Print)978-3-540-72846-7
Publication statusPublished - 2007
Event3rd Iberian Conference on Pattern Recognition and Image Analysis - Girona, Spain
Duration: 06 Jun 200708 Jun 2007

Conference

Conference3rd Iberian Conference on Pattern Recognition and Image Analysis
CountrySpain
CityGirona
Period06/06/200708/06/2007

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Martinez-del-Rincon, J., Orrite-Urunuela, C., & Rogez, G. (2007). Rao-blackwellized particle filter for human appearance and position tracking. In J. Marti, JM. Benedi, AM. Mendonca, & J. Serrat (Eds.), Pattern Recognition and Image Analysis, Pt 1, Proceedings (PART 1 ed., Vol. 4477 LNCS, pp. 201-208). Springer.