Optimising rPPG Signal Extraction by Exploiting Facial Surface Orientation

Kwan Long Wong, Jing Wei Chin, Tsz Tai Chan, Ismoil Odinaev, Kristian Suhartono, Kang Tianqu, Richard H.Y. So; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022, pp. 2165-2171

Remote photoplethysmography (rPPG) is a contactless method to measure human vital signs by detecting subtle skin color changes through a camera. Although many studies have used region of interest (ROI) selection tools to improve rPPG signal extraction, no study has investigated the influence of the ROI's surface orientation. We propose a novel 'angle map' representation of the face to study the effects of the surface orientation on the extracted rPPG signal. The angle map is generated by mapping each facial pixel to an angle of reflection (angle between the skin surface and the camera) calculated from the surface normal of the facial landmarks and the camera axis. Our results show that surface orientation significantly affects the correlation between the extracted rPPG signal and ground truth blood volume pulse (BVP). Regions with small angles of reflection contained stronger signals, which explains why areas near the cheeks and forehead are often chosen for rPPG signal extraction. Moreover, we applied a thresholding method to the angle map and demonstrated its potential for dynamic ROI selection, thereby optimising the rPPG signal extraction process.