Comparison of region of interest segmentation methods for video-based heart rate measurements

International audienceConventional contact photoplethysmography (PPG) sensors are not suitable in situations of skin damage or when unconstrained movement is required. As a consequence, remote photoplethysmography (rPPG) has recently emerged because it provides remote physiological measurements without expensive hardware and improves comfort for long-term monitoring. RPPG estimation methods use the spatially averaged RGB values of pixels in a Region Of Interest (ROI) to generate a temporal RGB signal. The selection of ROI is a critical first step to obtain reliable pulse signals and must contain as many skin pixels as possible with a low percentage of non-skin pixels. In this paper, we experimentally compare seven ROI segmentation methods in the perspective of heart rate (HR) measurements with dedicated metrics. The algorithms are compared using our in-house database UBFC-RPPG, comprising of 53 videos specifically geared towards rPPG analysis