Facial microexpression recognition based on adaptive key frame representation

Zhihua Xie; Xinhe Yu; Jieyi Niu; Yi Li

doi:10.1117/1.JEI.28.3.033015

23 May 2019 Facial microexpression recognition based on adaptive key frame representation

Zhihua Xie, Xinhe Yu, Jieyi Niu, Yi Li

Author Affiliations +

Journal of Electronic Imaging, Vol. 28, Issue 3, 033015 (May 2019). https://doi.org/10.1117/1.JEI.28.3.033015

Abstract

Recognizing microexpression serves as a vital clue for affective estimation. Fast and discriminative feature extraction has always been a critical issue for spontaneous microexpression recognition applications. A microexpression analysis framework is proposed by adaptively key frame extraction and representation. First, to remove redundant information in the microexpression video sequences, the key frame is adaptively selected on the criteria of structural similarity index between different face images, Second, robust principal component analysis is applied to obtain the sparse information in the key frame, which not only retains the expression attributes of the microexpression sequence, but also eliminates useless interference. Furthermore, we construct dual-cross patterns to get the final microexpressions representation for classification. Repeated comparison experiments were performed on the SMIC and CASME2 databases to evaluate the performance of the proposed method. Experimental results demonstrate that our proposed method gets higher recognition rates and achieves promising performance, compared with the traditional microexpression recognition.

Citation Download Citation

Zhihua Xie, Xinhe Yu, Jieyi Niu, and Yi Li "Facial microexpression recognition based on adaptive key frame representation," Journal of Electronic Imaging 28(3), 033015 (23 May 2019). https://doi.org/10.1117/1.JEI.28.3.033015

Received: 16 January 2019; Accepted: 6 May 2019; Published: 23 May 2019

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