University of Oulu

Yu, Z., Li, X., Zhao, G., Remote Photoplethysmograph Signal Measurement from Facial Videos Using Spatio-Temporal Networks, 30th British Machine Visison Conference : BMVC 2019. 9th-12th September 2019, Cardiff, UK, p. 1-12

Remote photoplethysmograph signal measurement from facial videos using spatio-temporal networks

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Author: Yu, Zitong1; Li, Xiaobai1; Zhao, Guoying2
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu, FI-90014, Finland
2School of Information and Technology, Northwest University 710069, China
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.2 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202001162354
Language: English
Published: The British Machine Vision Conference (BMVC), 2019
Publish Date: 2020-01-16
Description:

Abstract

Recent studies demonstrated that the average heart rate (HR) can be measured from facial videos based on non-contact remote photoplethysmography (rPPG). However for many medical applications (e.g., atrial fibrillation (AF) detection) knowing only the average HR is not sufficient, and measuring precise rPPG signals from face for heart rate variability (HRV) analysis is needed. Here we propose an rPPG measurement method, which is the first work to use deep spatio-temporal networks for reconstructing precise rPPG signals from raw facial videos. With the constraint of trend-consistency with ground truth pulse curves, our method is able to recover rPPG signals with accurate pulse peaks. Comprehensive experiments are conducted on two benchmark datasets, and results demonstrate that our method can achieve superior performance on both HR and HRV levels comparing to the state-of-the-art methods. We also achieve promising results of using reconstructed rPPG signals for AF detection and emotion recognition.

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Pages: 1 - 12
Host publication: 30th British Machine Visison Conference : BMVC 2019. 9th-12th September 2019, Cardiff, UK
Conference: The British Machine Vision Conference
Type of Publication: D3 Professional conference proceedings
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
Subjects:
Copyright information: © 2019. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.