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PulseEdit: Editing Physiological Signal in Facial Videos for Privacy Protection

preprint
posted on 25.06.2021, 22:20 by Mingliang Chen, Xin Liao, Min Wu
Recent studies have shown that physiological signals can be remotely captured from human faces using a portable color camera under ambient light. This technology, namely remote photoplethysmography (rPPG), can be used to collect users' physiological status who are sitting in front of a camera, which may raise physiological privacy issues. To avoid the privacy abuse of the rPPG technology, this paper develops PulseEdit, a novel and efficient algorithm that can edit the physiological signals in facial videos without affecting visual appearance to protect the user's physiological signal from disclosure. PulseEdit can either remove the trace of the physiological signal in a video or transform the video to contain a target physiological signal chosen by a user. Experimental results show that PulseEdit can effectively edit physiological signals in facial videos and prevent heart rate measurement based on rPPG. It is possible to utilize PulseEdit in adversarial scenarios against some rPPG-based visual security algorithms. We present analyses on the performance of PulseEdit against rPPG-based liveness detection and rPPG-based deepfake detection, and demonstrate its ability to circumvent these visual security algorithms.

History

Email Address of Submitting Author

mchen126@terpmail.umd.edu

ORCID of Submitting Author

0000-0002-8247-7608

Submitting Author's Institution

ECE, University of Maryland

Submitting Author's Country

United States of America