Remote Photoplethysmography#

DepthPhys: Near-Infrared Remote Photoplethysmography in Driver Monitoring Systems

Subtle variations in the body can be used to detect underlying physiological signals from camera video data. Existing research in this space is largely focused on extracting physiological signals from traditional two-dimensional planar video data. This project explores how the addition of depth data may be used to augment the results of these approaches. In particular, a novel optical pathway is proposed for camera-based physiological sensing and is validated on a new dataset consisting of seven hours of three-dimensional volumetric near-infrared monochromatic video data. Both two-dimensional and three-dimensional signals are extracted from this dataset and the results of either approach are compared using state-of-the-art camera-based physiological sensing neural methods. These findings provide valuable and novel insight into the utility of three-dimensional signals for camera-based physiological sensing, as well as the capability and limitations of existing camera-based physiological sensing solutions when applied in a driver monitoring system application context.