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.
Originalsprog | Engelsk |
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Titel | Energy Minimization Methods in Computer Vision and Pattern Recognition : 7th International Conference, EMMCVPR 2009, Bonn, Germany, August 24-27, 2009. Proceedings |
Redaktører | Daniel Cremers, Yuri Boykov, Andrew Blake, Frank R. Schmidt |
Antal sider | 14 |
Forlag | Springer |
Publikationsdato | 2009 |
Sider | 235-248 |
ISBN (Trykt) | 978-3-642-03640-8 |
ISBN (Elektronisk) | 978-3-642-03641-5 |
DOI | |
Status | Udgivet - 2009 |
Begivenhed | 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition - Bonn, Tyskland Varighed: 24 aug. 2009 → 27 aug. 2009 Konferencens nummer: 7 |
Konference
Konference | 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition |
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Nummer | 7 |
Land/Område | Tyskland |
By | Bonn |
Periode | 24/08/2009 → 27/08/2009 |
Navn | Lecture notes in computer science |
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Vol/bind | 5681 |
ISSN | 0302-9743 |
Emneord
- Det Natur- og Biovidenskabelige Fakultet