University of Oulu

Z. Xia, X. Feng, X. Hong and G. Zhao, "Spontaneous Facial Micro-expression Recognition via Deep Convolutional Network," 2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA), Xi’an, 2018, pp. 1-6. doi: 10.1109/IPTA.2018.8608119

Spontaneous facial micro-expression recognition via deep convolutional network

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Author: Xia, Zhaoqiang1; Feng, Xiaoyi1; Hong, Xiaopeng2;
Organizations: 1School of Electronics and Information, Northwestern Polytechnical University
2Center for Machine Vision and Signal Analysis, University of Oulu
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.6 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2018
Publish Date: 2019-08-05


The automatic recognition of spontaneous facial micro-expressions becomes prevalent as it reveals the actual emotion of humans. However, handcrafted features employed for recognizing micro-expressions are designed for general applications and thus cannot well capture the subtle facial deformations of micro-expressions. To address this problem, we propose an end-to-end deep learning framework to suit the particular needs of micro-expression recognition (MER). In the deep model, re- current convolutional networks are utilized to learn the representation of subtle changes from image sequences. To guarantee the learning of deep model, we present a temporal jittering procedure to greatly enrich the training samples. Through performing the experiments on three spontaneous micro-expression datasets, i.e., SMIC, CASME, and CASME2, we verify the effectiveness of our proposed MER approach.

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Series: Proceedings. International Workshops on Image Processing Theory, Tools, and Applications
ISSN: 2154-5111
ISSN-E: 2154-512X
ISSN-L: 2154-5111
ISBN: 978-1-5386-6428-5
ISBN Print: 978-1-5386-6429-2
Pages: 235 - 240
DOI: 10.1109/IPTA.2018.8608119
Host publication: 2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA)
Conference: International Conference on Image Processing Theory, Tools and Applications
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
Funding: This work is partly supported by the National Nature Science Foundation of China (No.61702419), and the Natural Science Basic Research Plan in Shaanxi Province of China (No.2018JQ6090).
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