Three dimensional monocular human motion analysis in end-effector space

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

7 Citationer (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.
OriginalsprogEngelsk
TitelEnergy Minimization Methods in Computer Vision and Pattern Recognition : 7th International Conference, EMMCVPR 2009, Bonn, Germany, August 24-27, 2009. Proceedings
RedaktørerDaniel Cremers, Yuri Boykov, Andrew Blake, Frank R. Schmidt
Antal sider14
ForlagSpringer
Publikationsdato2009
Sider235-248
ISBN (Trykt)978-3-642-03640-8
ISBN (Elektronisk)978-3-642-03641-5
DOI
StatusUdgivet - 2009
Begivenhed7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition - Bonn, Tyskland
Varighed: 24 aug. 200927 aug. 2009
Konferencens nummer: 7

Konference

Konference7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Nummer7
Land/OmrådeTyskland
ByBonn
Periode24/08/200927/08/2009
NavnLecture notes in computer science
Vol/bind5681
ISSN0302-9743

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  • Det Natur- og Biovidenskabelige Fakultet

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