University of Oulu

X. Li et al., "The 1st Challenge on Remote Physiological Signal Sensing (RePSS)," 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, WA, USA, 2020, pp. 1274-1281, doi: 10.1109/CVPRW50498.2020.00165

The 1st challenge on remote physiological signal sensing (RePSS)

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Author: Li, Xiaobai1; Han, Hu2; Niu, Xuesong2;
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu, Finland
2Institute of Computing Technology, CAS. China
3STARS team, INRIA, France
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2 MB)
Persistent link:
Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2021-02-19


Remote measurement of physiological signals from videos is an emerging topic. The topic draws great interests, but the lack of publicly available benchmark databases and a fair validation platform are hindering its further development. For this concern, we organize the first challenge on Remote Physiological Signal Sensing (RePSS), in which two databases of VIPL and OBF are provided as the benchmark for kin researchers to evaluate their approaches. The 1st challenge of RePSS focuses on measuring the average heart rate from facial videos, which is the basic problem of remote physiological measurement. This paper presents an overview of the challenge, including data, protocol, analysis of results and discussion. The top ranked solutions are highlighted to provide insights for researchers, and future directions are outlined for this topic and this challenge.

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Series: IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops
ISSN: 2160-7508
ISSN-E: 2160-7516
ISSN-L: 2160-7508
ISBN: 978-1-7281-9360-1
ISBN Print: 978-1-7281-9361-8
Pages: 1274 - 1281
Article number: 9150698
DOI: 10.1109/CVPRW50498.2020.00165
Host publication: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Conference: IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
Funding: Xiaobai Li and Guoying Zhao’s work were supported by National Natural Science Foundation of China (Grant 61772419), and Academy of Finland (Grant 316765 and 323287). Hu Han’s work was supported in part by Natural Science Foundation of China (Grant 61672496).
Academy of Finland Grant Number: 316765
Detailed Information: 316765 (Academy of Finland Funding decision)
323287 (Academy of Finland Funding decision)
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