The Impact of Video Compression on Remote Cardiac Pulse Measurement Using Imaging Photoplethysmography

Remote physiological measurement has great potential in healthcare and affective computing applications. Imaging photoplethysmography (iPPG) leverages digital cameras to recover the blood volume pulse from the human body. While the impact of video parameters such as resolution and frame rate on iPPG accuracy have been studied, there has not been a systematic analysis of video compression algorithms. We compared a set of commonly used video compression algorithms (x264 and x265) and varied the Constant Rate Factor (CRF) to measure pulse rate recovery for a range of bit rates (file sizes) and video qualities. We found that compression, even at a low CRF, degrades the blood volume pulse (BVP) signal-to-noise ratio considerably. However, the bit rate of a video can be substantially decreased (by a factor of over 1000) without destroying the BVP signal entirely. We found an approximately linear relationship between bit rate and BVP signal-to-noise ratio up to a CRF of 36. A faster decrease in SNR was observed for videos of the task involving larger head motions and the x265 algorithm appeared to work more effectively in these cases.