The 1st challenge on Remote Physiological Signal Sensing (RePSS)

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.

Authors:
Li Xiaobai, Han Hu, Niu Xuesong, Yu Zitong, Dantcheva Antitza, Zhao Guoying, Shan Shiguang

Publication type:
A4 Article in conference proceedings

Place of publication:
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Keywords:
6G Publication

Published:

Full citation:
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

DOI:
https://doi.org/10.1109/CVPRW50498.2020.00165

Read the publication here:
http://urn.fi/urn:nbn:fi-fe202102195372