Automatic Region-Based Heart Rate Measurement Using Remote Photoplethysmography

Benjamin Kossack, Eric L. Wisotzky, Anna Hilsmann, Peter Eisert

ICCVW 2021 pp. 2755-2759

doi:10.1109/ICCVW54120.2021.00309 /iccvw/2021/kossack2021iccvw-automatic/

Abstract

This paper presents a model-based approach to measure the vital signs from RGB video files focusing on the heart rate. We use the plane-orthogonal-to-skin (POS) remote photoplethysmography (rPPG) transformation performed individually at five well-defined regions of interest (ROI) in the face. We extract the heart rate information by a correlation of the different rPPG signals in these ROIs and a magnitude-based reliability calculation. This increases the robustness of the heart rate extraction from videos. With this method, we achieve a mean of all calculated mean-absolute-errors of 8.324 BPM in the V4V-Challenge data (averaged over all videos of the training and validation set).

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Cite

Text

Kossack et al. "Automatic Region-Based Heart Rate Measurement Using Remote Photoplethysmography." IEEE/CVF International Conference on Computer Vision Workshops, 2021. doi:10.1109/ICCVW54120.2021.00309

Markdown

[Kossack et al. "Automatic Region-Based Heart Rate Measurement Using Remote Photoplethysmography." IEEE/CVF International Conference on Computer Vision Workshops, 2021.](https://mlanthology.org/iccvw/2021/kossack2021iccvw-automatic/) doi:10.1109/ICCVW54120.2021.00309

BibTeX

@inproceedings{kossack2021iccvw-automatic,
  title     = {{Automatic Region-Based Heart Rate Measurement Using Remote Photoplethysmography}},
  author    = {Kossack, Benjamin and Wisotzky, Eric L. and Hilsmann, Anna and Eisert, Peter},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2021},
  pages     = {2755-2759},
  doi       = {10.1109/ICCVW54120.2021.00309},
  url       = {https://mlanthology.org/iccvw/2021/kossack2021iccvw-automatic/}
}