Key result
Proposed facial physiological shielding achieves ~84% interference efficiency against ICA and CHROM methods.
Why the study?
Non-contact video-based physiological signal detection can unknowingly leak personal physiological parameters such as heart rate and heart rate variability, creating privacy or security concerns.
A proposed method successfully shields facial physiological information in videos, reducing the accuracy of remote heart rate detection algorithms to protect privacy.
May safeguard privacy in video-based monitoring; leaves open real-world validation before clinical use.
With the recent development of non-contact physiological signal detection methods based on videos, it is possible to obtain the physiological parameters through the ordinary video only, such as heart rate and its variability of an individual. Therefore, personal physiological information may be leaked unknowingly with the spread of videos, which may cause privacy or security problems. In this paper a new method is proposed, which can shield physiological information in the video without reducing the video quality significantly. Firstly, the principle of the most widely used physiological signal detection algorithm: remote photoplethysmography (rPPG) was analyzed. Then the region of interest (ROI) of face contain physiological information with high signal to noise ratio was selected. Two physiological information forgery operation: single-channel periodic noise addition with blur filtering and brightness fine-tuning are conducted on the ROIs. Finally, the processed ROI images are merged into video frames to obtain the processed video. Experiments were performed on the VIPL-HR video dataset. The interference efficiencies of the proposed method on two mainly used rPPG methods: Independent Component Analysis (ICA) and Chrominance-based Method (CHROM) are 82.9 % and 84.6 % respectively, which demonstrated the effectiveness of the proposed method.
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Zheng et al. (2022) studied this question. Shielding facial physiological information (SFPI) method vs. Original unprocessed video was evaluated on Interference efficiency against Independent Component Analysis (ICA) and Chrominance-based Method (CHROM). The proposed method for shielding facial physiological information achieved interference efficiencies of 82.9% and 84.6% against ICA and CHROM methods respectively on the VIPL-HR dataset.
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