Bob’s implementation of different rPPG algorithms¶
This module contains the implementation of different remote photoplesthymography (rPPG) algorithms:
Also, we provide scripts to infer the heart-rate from the pulse signals, and to evaluate global performance on a database.
Note that this package was first meant to be used with the Manhob HCI-Tagging (http://mahnob-db.eu/hci-tagging/) and COHFACE (http://www.idiap.ch/dataset/cohface) databases, but could easily be extended to other datasets.
You should download the aforementioned databases before trying to run anything below!
- Li’s CVPR14 user’s guide
- Li’s CVPR14 Python API
- CHROM user’s guide
- CHROM Python API
- 2SR user’s guide
- 2SR Python API
- Retrieve the heart-rate and compute performances
Li X, Chen J, Zhao G & Pietikäinen M. Remote heart rate measurement from face videos under realistic situations IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. pdf
de Haan, G. & Jeanne, V. Robust Pulse Rate from Chrominance based rPPG IEEE Transactions on Biomedical Engineering, 2013. pdf
Wang, W., Stuijk, S. and de Haan, G. A Novel Algorithm for Remote Photoplesthymograpy: Spatial Subspace Rotation IEEE Trans. On Biomedical Engineering, 2015