A Reproducible Study on Remote Heart Rate Measurement
arXiv:1709.00962
Abstract
This paper studies the problem of reproducible research in remote photoplethysmography (rPPG). Most of the work published in this domain is assessed on privately-owned databases, making it difficult to evaluate proposed algorithms in a standard and principled manner. As a consequence, we present a new, publicly available database containing a relatively large number of subjects recorded under two different lighting conditions. Also, three state-of-the-art rPPG algorithms from the literature were selected, implemented and released as open source free software. After a thorough, unbiased experimental evaluation in various settings, it is shown that none of the selected algorithms is precise enough to be used in a real-world scenario.
Cited by in corpus (4)
- Real-time Webcam Heart-Rate and Variability Estimation with Clean Ground Truth for Evaluation
- DeepFakesON-Phys: DeepFakes Detection based on Heart Rate Estimation
- The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video
- MOMBAT: Heart Rate Monitoring from Face Video using Pulse Modeling and Bayesian Tracking