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Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

Peng, M; Wang, C; Chen, T; Liu, G; Fu, X; (2017) Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition. Frontiers in Psychology , 8 , Article 1745. 10.3389/fpsyg.2017.01745. Green open access

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Abstract

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Type: Article
Title: Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fpsyg.2017.01745
Publisher version: https://doi.org/10.3389/fpsyg.2017.01745
Language: English
Additional information: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10045102
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