标题：Macro-to-micro transformation model for micro-expression recognition
作者：Jia, Xitong; Ben, Xianye; Yuan, Hui; Kpalma, Kidiyo; Meng, Weixiao
作者机构：[Jia, Xitong; Ben, Xianye; Yuan, Hui] Shandong Univ, Sch Informat Sci & Engn, 27 Shanda South Rd, Jinan 250100, Shandong, Peoples R China.; [Kpalma, 更多
通讯作者地址：[Ben, XY]Shandong Univ, Sch Informat Sci & Engn, 27 Shanda South Rd, Jinan 250100, Shandong, Peoples R China.
来源：JOURNAL OF COMPUTATIONAL SCIENCE
关键词：Micro-expression recognition; Macro-to-micro transformation model;; Feature selection; Singular value decomposition
摘要：As one of the most important forms of psychological behaviors, micro-expression can reveal the real emotion. However, the existing labeled training samples are limited to train a high performance model. To overcome this limit, in this paper we propose a macro-to-micro transformation model which enables to transfer macro-expression learning to micro-expression. Doing so improves the efficiency of the micro expression features. For this purpose, LBP and LBP-TOP are used to extract macro-expression features and micro-expression features, respectively. Furthermore, feature selection is employed to reduce redundant features. Finally, singular value decomposition is employed to achieve macro-to-micro transformation model. The experimental evaluation based on the incorporated database including CK+ and CASME2 demonstrates that the proposed model achieves a competitive performance compared with the existing micro-expression recognition methods. (C) 2017 Elsevier B.V. All rights reserved.