MER-GCN: Micro-Expression Recognition Based on Relation Modeling with Graph Convolutional Networks

Ling Lo, Hong Xia Xie, Hong Han Shuai, Wen Huang Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Micro-Expression (ME) is the spontaneous, involuntary movement of a face that can reveal the true feeling. Recently, increasing researches have paid attention to this field combing deep learning techniques. Action units (AUs) are the fundamental actions reflecting the facial muscle movements and AU detection has been adopted by many researches to classify facial expressions. However, the time-consuming annotation process makes it difficult to correlate the combinations of AUs to specific emotion classes. Inspired by the nodes relationship building Graph Convolutional Networks (GCN), we propose an end-To-end AU-oriented graph classification network, namely MER-GCN, which uses 3D ConvNets to extract AU features and applies GCN layers to discover the dependency laying between AU nodes for ME categorization. To our best knowl-edge, this work is the first end-To-end architecture for Micro-Expression Recognition (MER) using AUs based GCN. The experimental results show that our approach outperforms CNN-based MER networks.

Original languageEnglish
Title of host publicationProceedings - 3rd International Conference on Multimedia Information Processing and Retrieval, MIPR 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages79-84
Number of pages6
ISBN (Electronic)9781728142722
DOIs
StatePublished - Aug 2020
Event3rd International Conference on Multimedia Information Processing and Retrieval, MIPR 2020 - Shenzhen, Guangdong, China
Duration: 6 Aug 20208 Aug 2020

Publication series

NameProceedings - 3rd International Conference on Multimedia Information Processing and Retrieval, MIPR 2020

Conference

Conference3rd International Conference on Multimedia Information Processing and Retrieval, MIPR 2020
CountryChina
CityShenzhen, Guangdong
Period6/08/208/08/20

Keywords

  • 3D ConvNets
  • AU
  • GCN
  • MER

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