Abstract
This paper presents a novel approach for model-based real-time tracking of highly articulated structures such as humans. This approach is based on an algorithm which efficiently propagates statistics of probability distributions through a kinematic chain to obtain maximum a posteriori estimates of the motion of the entire structure. This algorithm yields the least squares solution in linear time (in the number of components of the model) and can also be applied to non-Gaussian statistics using a simple but powerful trick. The resulting implementation runs in real-time on standard hardware without any pre-processing of the video data and can thus operate on live video. Results from experiments performed using this system are presented and discussed.
Original language | English |
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Pages | 315-320 |
Number of pages | 6 |
Publication status | Published - 1 Jan 2001 |
Externally published | Yes |
Event | IEEE International Conference on Computer Vision 2001 - Vancouver, Canada Duration: 7 Jul 2001 → 14 Jul 2001 Conference number: 8th https://ieeexplore.ieee.org/xpl/conhome/7460/proceeding?isnumber=20293 (Proceedings) |
Conference
Conference | IEEE International Conference on Computer Vision 2001 |
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Abbreviated title | ICCV 2001 |
Country/Territory | Canada |
City | Vancouver |
Period | 7/07/01 → 14/07/01 |
Internet address |