Remote Heart Rate Measurement through Broadband Video via Stochastic Bayesian Estimation

Abstract

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.