  Remote photoplethysmography (rPPG) is an attractive method for noninvasive,
convenient and concomitant measurement of physiological vital signals. Public
benchmark datasets have served a valuable role in the development of this
technology and improvements in accuracy over recent years.However, there remain
gaps in the public datasets.First, despite the ubiquity of cameras on mobile
devices, there are few datasets recorded specifically with mobile phone
cameras. Second, most datasets are relatively small and therefore are limited
in diversity, both in appearance (e.g., skin tone), behaviors (e.g., motion)
and environment (e.g., lighting conditions). In an effort to help the field
advance, we present the Multi-domain Mobile Video Physiology Dataset (MMPD),
comprising 11 hours of recordings from mobile phones of 33 subjects. The
dataset is designed to capture videos with greater representation across skin
tone, body motion, and lighting conditions. MMPD is comprehensive with eight
descriptive labels and can be used in conjunction with the rPPG-toolbox. The
reliability of the dataset is verified by mainstream unsupervised methods and
neural methods. The GitHub repository of our dataset:
https://github.com/THU-CS-PI/MMPD_rPPG_dataset.
