Micro-Expression Recognition by Leveraging Color Space Information

Minghao TANG  Yuan ZONG  Wenming ZHENG  Jisheng DAI  Jingang SHI  Peng SONG  

IEICE TRANSACTIONS on Information and Systems   Vol.E102-D   No.6   pp.1222-1226
Publication Date: 2019/06/01
Publicized: 2019/03/13
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDL8220
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
spontaneous micro-expression recognition,  color space,  fusiong learning,  

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Micro-expression is one type of special facial expressions and usually occurs when people try to hide their true emotions. Therefore, recognizing micro-expressions has potential values in lots of applications, e.g., lie detection. In this letter, we focus on such a meaningful topic and investigate how to make full advantage of the color information provided by the micro-expression samples to deal with the micro-expression recognition (MER) problem. To this end, we propose a novel method called color space fusion learning (CSFL) model to fuse the spatiotemporal features extracted in different color space such that the fused spatiotemporal features would be better at describing micro-expressions. To verify the effectiveness of the proposed CSFL method, extensive MER experiments on a widely-used spatiotemporal micro-expression database SMIC is conducted. The experimental results show that the CSFL can significantly improve the performance of spatiotemporal features in coping with MER tasks.