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Tracking Articulated Bodies Using Generalized Expectation Maximization

Andrea Fossati, Elise Arnaud, Radu Horaud, Pascal Fua
CVPRW 2008 pp. 1-6
doi:10.1109/CVPRW.2008.4563073 /cvprw/2008/fossati2008cvprw-tracking/

Abstract

A generalized expectation maximization (GEM) algorithm is used to retrieve the pose of a person from a monocular video sequence shot with a moving camera. After embedding the set of possible poses in a low dimensional space using principal component analysis, the configuration that gives the best match to the input image is held as estimate for the current frame. This match is computed iterating GEM to assign edge pixels to the correct body part and to find the body pose that maximizes the likelihood of the assignments.

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Cite

Text

Fossati et al. "Tracking Articulated Bodies Using Generalized Expectation Maximization." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008. doi:10.1109/CVPRW.2008.4563073

Markdown

[Fossati et al. "Tracking Articulated Bodies Using Generalized Expectation Maximization." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2008.](https://mlanthology.org/cvprw/2008/fossati2008cvprw-tracking/) doi:10.1109/CVPRW.2008.4563073

BibTeX

@inproceedings{fossati2008cvprw-tracking,
  title     = {{Tracking Articulated Bodies Using Generalized Expectation Maximization}},
  author    = {Fossati, Andrea and Arnaud, Elise and Horaud, Radu and Fua, Pascal},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2008},
  pages     = {1-6},
  doi       = {10.1109/CVPRW.2008.4563073},
  url       = {https://mlanthology.org/cvprw/2008/fossati2008cvprw-tracking/}
}