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.
See John, Yap Moi Hoon, Li Jingting, Hong Xiaopeng, Wang Su-Jing
A4 Article in conference proceedings
Place of publication:
14th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2019, 14-18 May 2019, Lille, France
J. See, M. H. Yap, J. Li, X. Hong and S. Wang, “MEGC 2019 – The Second Facial Micro-Expressions Grand Challenge,” 2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019), Lille, France, 2019, pp. 1-5. doi: 10.1109/FG.2019.8756611
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