Papers › A Reproducible Study on Remote Heart Rate Measurement

A Reproducible Study on Remote Heart Rate Measurement

4 Sep 2017arXiv:1709.00962archive 2025-07-28

Guillaume Heusch, André Anjos, Sébastien Marcel

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.

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dalaoplan/Happy-rPPG-Toolkit mentioned on GitHubpytorch report
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