Eliminating Physiological Information from Facial Videos

Abstract

Vital signs, cognitive load, and stress can be remotely measured from human faces using video-capturing devices under ambient light, which raises both wide applications and privacy issues. To avoid immoral use of this technology, there is a need for methods to eliminate physiological information from facial videos without affecting their visual appearance. To meet the need, we develop a novel algorithm based on motion component magnification that inputs a video and outputs its replica with physiological signals removed. Facial video data has been collected from 18 participants in a study to assess the performance of our algorithm in thwarting heart rate measurement based on remote photoplethysmography. Our results show that the mean absolute error of heart rate measurement averaged among participants was increased from 0.254 beats per minute to above 17 beats per minute without causing visible artifact. This is the first demonstration of an algorithm that can achieve this kind of functionality.