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

John See johnsee at mmu.edu.my
Thu Dec 6 20:59:13 -05 2018

[Apologies if you receive multiple copies of this CFP]

*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.


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

*http://bit.ly/CFP_MEGC2019 <http://bit.ly/CFP_MEGC2019>*

Submission site is open, and accessible at:

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.)

27 January 2019: Submission deadline
12 February 2019: Notification of acceptance
15 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) or John
See (johnsee at mmu.edu.my)
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