Automatic heart rate estimation from painful faces

Non-contact measurement of the heart rate is more comfortable than classical methods and can facilitate new applications. However, current approaches are very susceptible to motion. Aiming at overcoming this limitation, we propose a new, more robust approach to estimate the heart rate from a videotaped face. It features non-planar motion compensation, fusion of multiple ROI signals, and a RANSAC-like time-domain heart rate estimation algorithm. In experiments with a comprehensive pain recognition dataset we show that our approach outperforms previous methods in the presence of spontaneous head movement and facial expression.