Spontaneous facial micro-expression recognition via deep convolutional network
Xia, Zhaoqiang; Feng, Xiaoyi; Hong, Xiaopeng; Zhao, Guoying (2019-01-14)
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
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https://urn.fi/URN:NBN:fi-fe2019080523436
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Abstract
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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