[visionlist] [CFP] 2nd Facial Micro-Expression Grand Challenge (MEGC) Workshop @ IEEE FG 2019

Moi Hoon Yap M.Yap at mmu.ac.uk
Fri Jan 25 05:23:09 -05 2019


[Apologies if you receive multiple copies of this CFP]

CALL FOR PAPERS:
2nd Facial Micro-Expression Grand Challenge (MEGC) Workshop
in conjunction with the 14th IEEE Conference on Automatic Face and Gesture Recognition (FG) 2019
- Lille, France, 14-18 May 2019.

https://facial-micro-expressiongc.github.io/MEGC2019/

Facial micro-expressions (MEs) are involuntary movements of the face that occur spontaneously when a person experiences an emotion but attempts to suppress or repress the facial expression, typically found in a high-stakes environment. As such, the duration of MEs is very short with the general duration of not more than 500 milliseconds (ms), and is the telltale sign that distinguishes them from a normal facial expression. Computational analysis and automation of tasks on micro-expressions is an emerging area in face research, with a strong interest appearing as recent as 2014. Only recently, the availability of a few spontaneously induced facial micro-expression datasets has provided the impetus to advance further from the computational aspect. Particularly comprehensive are two state-of-the-art FACS coded datasets: the Chinese Academy of Sciences Micro-Expression Database II (CASME II) with 247 MFEs at 200 fps and the Spontaneous Facial Micro-Movement Dataset (SAMM) with 159 MFEs at 200 fps. In addition, there is recent interest in acquiring “in-the-wild” datasets to further introduce real-world scenarios. While much research has been done on these datasets individually, there have been little attempts to introduce a more rigorous and realistic evaluation to work done in this domain. This is the second edition of this workshop, which aims to promote interactions between researchers and scholars not only from within this niche area of facial micro-expression research, but also including those from broader, general areas of expression and psychology research.

This workshop has three main agendas:
1. To organize, for the first time, a Micro-Expression Spotting Challenge based on CAS(ME)^2 and SAMM datasets.
2. To organize the second Micro-Expression Cross-DB Recognition Challenge, which increases its previous coverage of CASME II and SAMM datasets to include the SMIC dataset.
3.To solicit original works that addresses a variety of challenges in ME research, but not limited to:

- ME Spotting / Detection
- ME Recognition
- ME Feature Representations & Computational Analysis
- Unified ME Spot-and-Recognize schemes
- Deep Learning Techniques for ME Analysis
- ME Data Synthesis
- New ME Datasets
- Real-world Applications of ME
- Computational Linkages to Psychology / Neuroscience in MEs

SUBMISSIONS
Submission site is open, and accessible at:
https://cmt3.research.microsoft.com/MEGC2019

Each paper will be reviewed by at least two reviewers from the TPC or external experts in "double-blind" fashion, and so the submitted version of the paper should be appropriately anonymized not to reveal the authors or authors’ institutions. The submitted papers should present original work, not currently under review elsewhere and should have no substantial overlap with already published work. All challenge entries should be accompanied by a paper submission.

Submissions (in PDF) can either be in the form of a short paper (max 4 pages + 1 page for reference) or long paper (no more than 8 pages including references) in IEEE FG 2019 paper format. See here<http://fg2019.org/participate/regular-papers/> for further instructions. Workshop papers presented at FG 2019 will appear in the IEEE Xplore digital library. If a paper is accepted, it is assumed that an author will register and attend the workshop to present the paper. (Papers that are not presented will not be published in the proceedings.)

Dates
27 January 2019   4 February 2019 Extended Submission deadline
21 February 2019: Notification of acceptance
26 February 2019:  Camera ready submission

Organizing Chairs
Moi Hoon Yap, Manchester Metropolitan University, UK
Sujing Wang, Chinese Academy of Sciences, China
John See, Multimedia University, Malaysia
Xiaopeng Hong, University of Oulu, Finland

Advisory Panel
Xiaolan Fu, Chinese Academy of Sciences, China
Guoying Zhao, University of Oulu, Finland

===
For further enquries, please contact Moi Hoon Yap (m.yap at mmu.ac.uk<mailto:m.yap at mmu.ac.uk>) or John See (johnsee at mmu.edu.my<mailto:johnsee at mmu.edu.my>)
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