Image Enhancement for Remote Photoplethysmography in a Low-Light
Environment
- URL: http://arxiv.org/abs/2303.09336v1
- Date: Thu, 16 Mar 2023 14:18:48 GMT
- Title: Image Enhancement for Remote Photoplethysmography in a Low-Light
Environment
- Authors: Lin Xi, Weihai Chen, Changchen Zhao, Xingming Wu, and Jianhua Wang
- Abstract summary: The accuracy of remote heart rate monitoring technology has been significantly improved.
Despite the significant algorithmic advances, the performance of r algorithm can degrade in the long-term.
Insufficient lighting in video capturing hurts quality of physiological signal.
The proposed solution for r process is effective to detect and improve the signal-to-noise ratio and precision of the pulsatile signal.
- Score: 13.740047263242575
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: With the improvement of sensor technology and significant algorithmic
advances, the accuracy of remote heart rate monitoring technology has been
significantly improved. Despite of the significant algorithmic advances, the
performance of rPPG algorithm can degrade in the long-term, high-intensity
continuous work occurred in evenings or insufficient light environments. One of
the main challenges is that the lost facial details and low contrast cause the
failure of detection and tracking. Also, insufficient lighting in video
capturing hurts the quality of physiological signal. In this paper, we collect
a large-scale dataset that was designed for remote heart rate estimation
recorded with various illumination variations to evaluate the performance of
the rPPG algorithm (Green, ICA, and POS). We also propose a low-light
enhancement solution (technical solution) for remote heart rate estimation
under the low-light condition. Using collected dataset, we found 1) face
detection algorithm cannot detect faces in video captured in low light
conditions; 2) A decrease in the amplitude of the pulsatile signal will lead to
the noise signal to be in the dominant position; and 3) the chrominance-based
method suffers from the limitation in the assumption about skin-tone will not
hold, and Green and ICA method receive less influence than POS in dark
illuminance environment. The proposed solution for rPPG process is effective to
detect and improve the signal-to-noise ratio and precision of the pulsatile
signal.
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