SMEConvNet: A Convolutional Neural Network for Spotting Spontaneous Facial Micro-Expression From Long Videos
文献类型:期刊论文
作者 | Zhang, Zhihao1,2; Chen, Tong1,2,3; Meng, Hongying1,4; Liu, Guangyuan1,2; Fu, Xiaolan3,5![]() ![]() |
刊名 | IEEE ACCESS
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出版日期 | 2018 |
卷号 | 6页码:71143-71151 |
关键词 | Spotting micro-expression apex frame convolutional neural network deep learning |
ISSN号 | 2169-3536 |
DOI | 10.1109/ACCESS.2018.2879485 |
通讯作者 | Chen, Tong(c_tong@swu.edu.cn) |
英文摘要 | Micro-expression is a subtle and involuntary facial expression that may reveal the hidden emotion of human beings. Spotting micro-expression means to locate the moment when the micro-expression happens, which is a primary step for micro-expression recognition. Previous work in micro-expression spotting focus on spotting micro-expression from short video, and with hand-crafted features. In this paper, we present a methodology for spotting micro-expression from long videos. Specifically, a new convolutional neural network named spotting micro-expression convolutional network was designed for extracting features from video clips, which is the first time that deep learning is used in micro-expression spotting. Then, a feature matrix processing method was proposed for spotting the apex frame from long video, which uses a sliding window and takes the characteristics of micro-expression into account to search the apex frame. Experimental results demonstrate that the proposed method can achieve a better performance than the existing state-of-art methods. |
WOS关键词 | RECOGNITION |
资助项目 | National Natural Science Foundation of China[61301297] ; National Natural Science Foundation of China[61502398] ; National Natural Science Foundation of China (NSFC) ; German Research Foundation (DFG)[NSFC 6162113608/DFG TRR-169] |
WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
语种 | 英语 |
WOS记录号 | WOS:000453304600001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
资助机构 | National Natural Science Foundation of China ; National Natural Science Foundation of China (NSFC) ; German Research Foundation (DFG) |
源URL | [http://ir.psych.ac.cn/handle/311026/27769] ![]() |
专题 | 心理研究所_认知与发展心理学研究室 |
通讯作者 | Chen, Tong |
作者单位 | 1.Southwest Univ, Chongqing Key Lab Nonlinear Circuit & Intelligent, Chongqing 400715, Peoples R China 2.Chongqing Key Lab Artificial Intelligence & Serv, Chongqing 400715, Peoples R China 3.Chinese Acad Sci, Inst Psychol, Beijing 100101, Peoples R China 4.Brunel Univ London, Dept Elect & Comp Engn, London UB8 3PH, England 5.Univ Chinese Acad Sci, Dept Psychol, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Zhihao,Chen, Tong,Meng, Hongying,et al. SMEConvNet: A Convolutional Neural Network for Spotting Spontaneous Facial Micro-Expression From Long Videos[J]. IEEE ACCESS,2018,6:71143-71151. |
APA | Zhang, Zhihao,Chen, Tong,Meng, Hongying,Liu, Guangyuan,Fu, Xiaolan,&Fu,Xiaolan.(2018).SMEConvNet: A Convolutional Neural Network for Spotting Spontaneous Facial Micro-Expression From Long Videos.IEEE ACCESS,6,71143-71151. |
MLA | Zhang, Zhihao,et al."SMEConvNet: A Convolutional Neural Network for Spotting Spontaneous Facial Micro-Expression From Long Videos".IEEE ACCESS 6(2018):71143-71151. |
入库方式: OAI收割
来源:心理研究所
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