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Found 2 papers, 1 papers with code
Image Enhancement for Remote Photoplethysmography in a Low-Light Environment
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.
Weighted combination and singular spectrum analysis based remote photoplethysmography pulse extraction in low-light environments
The test results verify that the proposed method has stronger robustness to low illumination than state-of-the-art methods, effectively improving the signal-to-noise ratio and heart rate estimation precision.
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