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 language | English |
---|---|
Title of host publication | Energy Minimization Methods in Computer Vision and Pattern Recognition : 7th International Conference, EMMCVPR 2009, Bonn, Germany, August 24-27, 2009. Proceedings |
Editors | Daniel Cremers, Yuri Boykov, Andrew Blake, Frank R. Schmidt |
Number of pages | 14 |
Publisher | Springer |
Publication date | 2009 |
Pages | 235-248 |
ISBN (Print) | 978-3-642-03640-8 |
ISBN (Electronic) | 978-3-642-03641-5 |
DOIs | |
Publication status | Published - 2009 |
Event | 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition - Bonn, Germany Duration: 24 Aug 2009 → 27 Aug 2009 Conference number: 7 |
Conference
Conference | 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition |
---|---|
Number | 7 |
Country/Territory | Germany |
City | Bonn |
Period | 24/08/2009 → 27/08/2009 |
Series | Lecture notes in computer science |
---|---|
Volume | 5681 |
ISSN | 0302-9743 |
Keywords
- Faculty of Science