AI RESEARCH
Reliability-Aware Weighted Multi-Scale Spatio-Temporal Maps for Heart Rate Monitoring
arXiv CS.CV
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ArXi:2603.26836v1 Announce Type: cross Remote photoplethysmography (rPPG) allows for the contactless estimation of physiological signals from facial videos by analyzing subtle skin color changes. However, rPPG signals are extremely susceptible to illumination changes, motion, shadows, and specular reflections, resulting in low-quality signals in unconstrained environments. To overcome these issues, we present a Reliability-Aware Weighted Multi-Scale Spatio-Temporal (WMST) map that models pixel reliability through the suppression of environmental noises.