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The 2nd challenge on remote physiological signal sensing (RePSS) |
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| Author: | Li, Xiaobai1; Sun, Haomiao2; Sun, Zhaodong1; |
| Organizations: |
1Center for Machine Vision and Signal Analysis, University of Oulu, Finland 2Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, China 3Peng Cheng Laboratory, Shenzhen, China
4STARS team, INRIA, France
52Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, China |
| Format: | article |
| Version: | accepted version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 3.8 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe202201041144 |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers,
2021
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| Publish Date: | 2022-01-04 |
| Description: |
AbstractRemote measurement of physiological signals from videos is an emerging topic. The topic draws great interest, but the lack of publicly available benchmark databases and a fair validation platform are hindering its further development. The RePSS Challenge is organized as an annual event for this concern. Here the 2nd RePSS is organized in conjunction with ICCV 2021. The 2nd RePSS contains two competition tracks. Track 1 is to measure inter-beat-intervals (IBI) from facial videos, which requires accurate measurement of each individual pulse peak. Track 2 is about respiration measurement from facial videos, as respiration is another important physiological index related to both health and emotional status. One new dataset is built and shared for Track 2. This paper presents an overview of the challenge, including data, protocol, results, and discussion. We highlighted the top-ranked solutions to provide insight for researchers, and we also outline future directions for this topic and this challenge. see all
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| Series: |
IEEE International Conference on Computer Vision workshops |
| ISSN: | 2473-9944 |
| ISSN-E: | 2473-9936 |
| ISSN-L: | 2473-9944 |
| ISBN: | 978-1-6654-0191-3 |
| ISBN Print: | 978-1-6654-0192-0 |
| Pages: | 2404 - 2413 |
| DOI: | 10.1109/ICCVW54120.2021.00273 |
| OADOI: | https://oadoi.org/10.1109/ICCVW54120.2021.00273 |
| Host publication: |
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 11-17 Oct. 2021, Montreal, BC, Canada |
| Conference: |
IEEE/CVF International Conference on Computer Vision Workshops |
| Type of Publication: |
B3 Article in conference proceedings |
| Field of Science: |
113 Computer and information sciences |
| Subjects: | |
| 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 323287 |
| Detailed Information: |
316765 (Academy of Finland Funding decision) 323287 (Academy of Finland Funding decision) |
| Copyright information: |
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