标题:Micro-expression recognition system
作者:Zhang, Peng; Ben, Xianye; Yan, Rui; Wu, Chen; Guo, Chang
作者机构:[Zhang, Peng; Ben, Xianye; Wu, Chen; Guo, Chang] Shandong Univ, Sch Informat Sci & Engn, Jinan 250100, Peoples R China.; [Yan, Rui] Rensselaer Polyt 更多
通讯作者:Ben, Xianye
通讯作者地址:[Ben, XY]Shandong Univ, Sch Informat Sci & Engn, 27 Shanda South Rd, Jinan 250100, Peoples R China.
来源:OPTIK
出版年:2016
卷:127
期:3
页码:1395-1400
DOI:10.1016/j.ijleo.2015.10.217
关键词:Micro-expression recognition; Visual platform; Gabor wavelet; Dimension; reduction; SVM
摘要:Micro-expressions are rapid involuntary facial expressions which reveal one's genuine emotions people trying to disguise. To the best of our knowledge, few works have been done in designing a micro-expression recognition visual platform. In this paper, we preliminarily study micro-expression recognition and subsequently develop a micro-expression visual platform that includes feature expression, dimension reduction as well as real-time video testing, etc. The platform leverages Gabor wavelet filter for expression feature extraction, principal components analysis (PCA) and linear discriminant analysis (LDA) for dimension reduction, and support vector machine (SVM) for expression classification. By using the trained model of the platform, we are able to test against micro-expression recognition. Experimental results show that the proposed scheme performs well on the CASME II database. Besides, it also works well on real-time expression recognition. (C) 2015 Elsevier GmbH. All rights reserved.
收录类别:EI;SCOPUS;SCIE
WOS核心被引频次:6
Scopus被引频次:8
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959320571&doi=10.1016%2fj.ijleo.2015.10.217&partnerID=40&md5=8ec712b921ad8fb7680c3f08e8a8af85
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