Three dimensional monocular human motion analysis in end-effector space

Søren Hauberg, Jerome Lapuyade, Morten Pol Engell-Nørregård, Kenny Erleben, Kim Steenstrup Pedersen

7 Citations (Scopus)
49 Downloads (Pure)

Abstract

In this paper, we present a novel approach to three dimensional human motion estimation from monocular video data. We employ a particle filter to perform the motion estimation. The novelty of the method lies in the choice of state space for the particle filter. Using a non-linear inverse kinematics solver allows us to perform the filtering in end-effector space. This effectively reduces the dimensionality of the state space while still allowing for the estimation of a large set of motions. Preliminary experiments with the strategy show good results compared to a full-pose tracker.
Original languageEnglish
Title of host publicationEnergy Minimization Methods in Computer Vision and Pattern Recognition : 7th International Conference, EMMCVPR 2009, Bonn, Germany, August 24-27, 2009. Proceedings
EditorsDaniel Cremers, Yuri Boykov, Andrew Blake, Frank R. Schmidt
Number of pages14
PublisherSpringer
Publication date2009
Pages235-248
ISBN (Print)978-3-642-03640-8
ISBN (Electronic)978-3-642-03641-5
DOIs
Publication statusPublished - 2009
Event7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition - Bonn, Germany
Duration: 24 Aug 200927 Aug 2009
Conference number: 7

Conference

Conference7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Number7
Country/TerritoryGermany
CityBonn
Period24/08/200927/08/2009
SeriesLecture notes in computer science
Volume5681
ISSN0302-9743

Keywords

  • Faculty of Science

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