Remote Heart Rate Measurement through Broadband Video via Stochastic Bayesian Estimation

A novel method for remote heart rate sensing via standard broadband video is proposed. Points are stochastically sampled from the cheek region and tracked throughout the video, producing a set of skin erythema time series. From these observations, a photoplethysmogram (PPG) is estimated via Bayesian minimization, with the required posterior probability estimated through an importanceweighted Monte Carlo approach. From the estimated PPG, an estimated heart rate is produced through frequency domain analysis. Results indicate improved accuracy over current state of the art methods.