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MEGC2020 : the third facial micro-expression grand challenge |
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| Author: | LI, Jingting1; Wang, Su-Jing1,2; Yap, Moi Hoon3; |
| Organizations: |
1Key Laboratory of Behavior Sciences, Institute of Psychology, Chinese Academy of Sciences, Beijing, China 2Department of Psychology, University of the Chinese Academy of Sciences, Beijing, China 3Faculty of Science and Engineering, Manchester Metropolitan University, UK
4Faculty of Computing and Informatics, Multimedia University, Malaysia
5Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, China 6Center for Machine Vision and Signal Analysis, University of Oulu, Finland |
| Format: | article |
| Version: | accepted version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 0.1 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe202103298641 |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers,
2020
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| Publish Date: | 2021-03-29 |
| Description: |
AbstractThe recent emergence of automatic facial micro-expression analysis has attracted a lot of attention in the last five years. Compared to the advances made in micro-expression recognition, the task of micro-expression spotting from long videos is tremendously in need of more effective methods. This paper summarises the 3rd Facial Micro-Expression Grand Challenge (MEGC 2020) held in conjunction with the 15th IEEE Conference on Automatic Face and Gesture Recognition (FG) 2020. In this workshop, we propose a new challenge of spotting both macro- and micro-expressions from long videos, to spur the community to develop new techniques for micro-expression spotting and also to extend facial micro-expression analysis to more complex real-world scenarios where micro-expressions are likely to be intertwined among normal expressions. In this paper, we outline the evaluation protocols for the challenge task, and describe the datasets involved. Then, we summarize the methods from the accepted challenge papers, present the comparison and analysis of results, as well as future directions. see all
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| ISBN: | 978-1-7281-3079-8 |
| ISBN Print: | 978-1-7281-3080-4 |
| Pages: | 777 - 780 |
| DOI: | 10.1109/FG47880.2020.00035 |
| OADOI: | https://oadoi.org/10.1109/FG47880.2020.00035 |
| Host publication: |
2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020) |
| Conference: |
IEEE International Conference on Automatic Face and Gesture Recognition |
| Type of Publication: |
B3 Article in conference proceedings |
| Field of Science: |
113 Computer and information sciences 213 Electronic, automation and communications engineering, electronics |
| Subjects: | |
| Funding: |
The workshop chairs would like to thank their funders: National Natural Science Foundation of China (U19B2032, 61772511, 61472138, 61572205), The UK Royal Society Industry Fellowship (IF160006), Shanghai ’The Belt and Road’ Young Scholar Exchange Grant (17510740100), Academic of Finland, Tekes, Infotech Oulu. |
| Copyright information: |
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