Gaze into the Heart: A Multi-View Video Dataset for rPPG and Health
  Biomarkers Estimation
Authors: name: Konstantin Egorov, name: Stepan Botman, name: Pavel Blinov, name: Galina Zubkova, name: Anton Ivaschenko, name: Alexander Kolsanov, name: Andrey Savchenko

Progress in remote PhotoPlethysmoGraphy (rPPG) is limited by the critical
issues of existing publicly available datasets: small size, privacy concerns
with facial videos, and lack of diversity in conditions. The paper introduces a
novel comprehensive large-scale multi-view video dataset for rPPG and health
biomarkers estimation. Our dataset comprises 3600 synchronized video recordings
from 600 subjects, captured under varied conditions (resting and post-exercise)
using multiple consumer-grade cameras at different angles. To enable multimodal
analysis of physiological states, each recording is paired with a 100 Hz PPG
signal and extended health metrics, such as electrocardiogram, arterial blood
pressure, biomarkers, temperature, oxygen saturation, respiratory rate, and
stress level. Using this data, we train an efficient rPPG model and compare its
quality with existing approaches in cross-dataset scenarios. The public release
of our dataset and model should significantly speed up the progress in the
development of AI medical assistants.