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

MMPD: Multi-Domain Mobile Video Physiology Dataset