PRNet

Illumination-robust rPPG heart-rate estimation via spatial-temporal transformer for robot-mounted cameras

A new arXiv paper presents an end-to-end spatial-temporal transformer framework for remote photoplethysmography (rPPG) heart-rate estimation that is robust to illumination variation, targeting robot-mounted RGB cameras. The system integrates 3D face alignment, illumination augmentation, a Residual Temporal Standardization Module, and a hybrid waveform-plus-spectral loss. On a new dataset spanning three illumination levels, the method achieves 0.79 bpm MAE and 0.982 HR correlation, reducing error by 93.6% relative to the PhysFormer baseline. The work is relevant to physiological sensing in service and assistive robotics.