ML Anthology

Unsupervised Learning of Human Body Parts from Video Footage

Thomas Walther, Rolf P. Würtz
ICCVW 2009 pp. 336-343
doi:10.1109/ICCVW.2009.5457680 /iccvw/2009/walther2009iccvw-unsupervised/

Abstract

Estimation of human body postures from video footage is still one of the most challenging tasks in computer vision. Even most recent approaches in this field rely strongly on domain knowledge provided by human supervisors and are nevertheless far from operating reliably under real-world conditions. We propose to overcome these issues by integrating principles of organic computing into the posture estimation cycle, thereby relegating the need for human intervention while simultaneously raising the level of system autonomy.

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Cite

Text

Walther and Würtz. "Unsupervised Learning of Human Body Parts from Video Footage." IEEE/CVF International Conference on Computer Vision Workshops, 2009. doi:10.1109/ICCVW.2009.5457680

Markdown

[Walther and Würtz. "Unsupervised Learning of Human Body Parts from Video Footage." IEEE/CVF International Conference on Computer Vision Workshops, 2009.](https://mlanthology.org/iccvw/2009/walther2009iccvw-unsupervised/) doi:10.1109/ICCVW.2009.5457680

BibTeX

@inproceedings{walther2009iccvw-unsupervised,
  title     = {{Unsupervised Learning of Human Body Parts from Video Footage}},
  author    = {Walther, Thomas and Würtz, Rolf P.},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2009},
  pages     = {336-343},
  doi       = {10.1109/ICCVW.2009.5457680},
  url       = {https://mlanthology.org/iccvw/2009/walther2009iccvw-unsupervised/}
}