On the diffusion process for heart rate estimation from face videos under realistic conditions

Abstract

This work addresses the problem of estimating heart rate from face videos under real conditions using a model based on the recursive inference problem that leverages the local invariance of the heart rate. The proposed solution is based on the canonical state space representation of an Itō process and a Wiener velocity model. Empirical results yield to excellent real-time and estimation performance of heart rate in presence of disturbing factors, like rigid head motion, talking and facial expressions under natural illumination conditions making the process of heart rate estimation from face videos applicable in a much broader sense. To facilitate comparisons and to support research we made the code and data for reproducing the results public available.