Color-distortion filtering for remote photoplethysmography

W. Wang, A.C. den Brinker, S. Stuijk, G. de Haan

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11 Citaten (Scopus)
102 Downloads (Pure)

Samenvatting

This paper introduces a powerful filtering method that exploits the physiological and optical properties of skin reflections to improve the performance of remote photoplethysmography (rPPG). Based on the fact that the pulsatile and non-pulsatile (e.g., intensity and specular changes) components have different reflection-spectra in a multi-wavelength camera, we propose to use their different characteristic color changes as a soft criterion to filter the RGB-signals in the frequency domain, such that the AC-components containing clear color distortions can be suppressed before the actual pulse extraction. This leads to a novel "Color-Distortion Filter" (CDF) that can be used as a common pre-processing step for arbitrary rPPG algorithms to increase their robustness. The benchmark in challenging fitness recordings shows that CDF brings significant and consistent improvements to all benchmarked rPPG algorithms, and drives all multi-channel approaches to a similar high quality-level.
Originele taal-2Engels
Titel12th IEEE Conference on Automatic Face and Gesture Recognition
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's71-78
Aantal pagina's8
ISBN van elektronische versie9781509040230
ISBN van geprinte versie978-1-5090-4023-0
DOI's
StatusGepubliceerd - 28 jun 2017
Evenement12th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017) - Washington DC, Verenigde Staten van Amerika
Duur: 30 mei 20173 jun 2017

Congres

Congres12th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017)
Verkorte titelFG2017
LandVerenigde Staten van Amerika
StadWashington DC
Periode30/05/173/06/17

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Citeer dit

Wang, W., den Brinker, A. C., Stuijk, S., & de Haan, G. (2017). Color-distortion filtering for remote photoplethysmography. In 12th IEEE Conference on Automatic Face and Gesture Recognition (blz. 71-78). [7961725] Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/FG.2017.18