ML Anthology

Pain Recognition Using Spatiotemporal Oriented Energy of Facial Muscles

Ramin Irani, Kamal Nasrollahi, Thomas B. Moeslund
CVPRW 2015 pp. 80-87
doi:10.1109/CVPRW.2015.7301340 /cvprw/2015/irani2015cvprw-pain/

Abstract

Pain is a critical sign in many medical situations and<br/>its automatic detection and recognition using computer vision<br/>techniques is of great importance. Utilizes this fact<br/>that pain is a spatiotemporal process, the proposed system<br/>in this paper employs steerable and separable filters<br/>to measures energies released by the facial muscles during<br/>the pain process. The proposed system not only detects the<br/>pain but recognizes its level. Experimental results on the<br/>publicly available pain database of UNBC show promising<br/>outcome for automatic pain detection and recognition.

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Cite

Text

Irani et al. "Pain Recognition Using Spatiotemporal Oriented Energy of Facial Muscles." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2015. doi:10.1109/CVPRW.2015.7301340

Markdown

[Irani et al. "Pain Recognition Using Spatiotemporal Oriented Energy of Facial Muscles." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2015.](https://mlanthology.org/cvprw/2015/irani2015cvprw-pain/) doi:10.1109/CVPRW.2015.7301340

BibTeX

@inproceedings{irani2015cvprw-pain,
  title     = {{Pain Recognition Using Spatiotemporal Oriented Energy of Facial Muscles}},
  author    = {Irani, Ramin and Nasrollahi, Kamal and Moeslund, Thomas B.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2015},
  pages     = {80-87},
  doi       = {10.1109/CVPRW.2015.7301340},
  url       = {https://mlanthology.org/cvprw/2015/irani2015cvprw-pain/}
}