MEGC 2019 - The second facial micro-expressions grand challenge

John See, Moi Hoon Yap, Jingting Li, Xiaopeng Hong, Su-Jing Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)

Abstract

Automatic facial micro-expression (ME) analysis is a growing field of research that has gained much attention in the last five years. With many recent works testing on limited data, there is a need to spur better approaches that are both robust and effective. This paper summarises the 2nd Facial Micro-Expression Grand Challenge (MEGC 2019) held in conjunction with the 14th IEEE Conference on Automatic Face and Gesture Recognition (FG) 2019. In this workshop, we proposed challenges for two micro-expression (ME) tasks-spotting and recognition, with the aim of encouraging rigorous evaluation and development of new robust techniques that can accommodate data captured across a variety of settings. In this paper, we outline the evaluation protocols for the two challenge tasks, the datasets involved, and an analysis of the best performing works from the participating teams, together with a summary of results. Finally, we highlight some possible future directions.

Original languageEnglish
Title of host publication14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019)
PublisherIEEE
ISBN (Electronic)9781728100890
DOIs
Publication statusPublished - 11 Jul 2019
Event14th IEEE International Conference on Automatic Face and Gesture Recognition 2019 - Lille, France
Duration: 14 May 201918 May 2019

Conference

Conference14th IEEE International Conference on Automatic Face and Gesture Recognition 2019
Abbreviated titleFG 2019
Country/TerritoryFrance
CityLille
Period14/05/1918/05/19

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Media Technology

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