ML Anthology

Predicting Brainwaves from Face Videos

Christian S. Pilz, Ibtissem Ben Makhlouf, Ute Habel, Steffen Leonhardt
CVPRW 2020 pp. 1139-1147
doi:10.1109/CVPRW50498.2020.00149 /cvprw/2020/pilz2020cvprw-predicting/

Abstract

We investigate the regulation of human brain arousal in the central nervous system and its synchronization with the autonomic nervous system affecting the facial dynamics and its behavioral gestalt. A major focus is made on the sensing observable during natural human eye to eye communication. Although the inner state of the autopoietic system is deterministic, its outer facial behavioral component nondeterministic. Beside the introduction of general validity of the classical empirical interpretation of the vigilance continuum during open eyes, we show that the facial behavior can be used as suitable surrogate measurement for specific states of mind. As a consequence we predict brainwaves from face videos formulated as inverse problem of the underlying stochastic process. Finally, we discuss the impact and range of application field.

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Cite

Text

Pilz et al. "Predicting Brainwaves from Face Videos." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020. doi:10.1109/CVPRW50498.2020.00149

Markdown

[Pilz et al. "Predicting Brainwaves from Face Videos." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020.](https://mlanthology.org/cvprw/2020/pilz2020cvprw-predicting/) doi:10.1109/CVPRW50498.2020.00149

BibTeX

@inproceedings{pilz2020cvprw-predicting,
  title     = {{Predicting Brainwaves from Face Videos}},
  author    = {Pilz, Christian S. and Makhlouf, Ibtissem Ben and Habel, Ute and Leonhardt, Steffen},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2020},
  pages     = {1139-1147},
  doi       = {10.1109/CVPRW50498.2020.00149},
  url       = {https://mlanthology.org/cvprw/2020/pilz2020cvprw-predicting/}
}