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A Main Directional Mean Optical Flow Feature for Spontaneous Micro-Expression Recognition
Liu, Yong-Jin1; Zhang, Jin-Kai1; Yan, Wen-Jing3; Wang, Su-Jing2; Zhao, Guoying4,5; Fu, Xiaolan2
2016-10-01
发表期刊IEEE Transactions on Affective Computing
ISSN1949-3045
文章类型Article
卷号7期号:4页码:299-310
摘要

Micro-expressions are brief facial movements characterized by short duration, involuntariness and low intensity. Recognition of spontaneous facial micro-expressions is a great challenge. In this paper, we propose a simple yet effective Main Directional Mean Optical-flow (MDMO) feature for micro-expression recognition. We apply a robust optical flow method on micro-expression video clips and partition the facial area into regions of interest (ROIs) based partially on action units. The MDMO is a ROI-based, normalized statistic feature that considers both local statistic motion information and its spatial location. One of the significant characteristics of MDMO is that its feature dimension is small. The length of a MDMO feature vector is 36 x 2 = 72, where 36 is the number of ROIs. Furthermore, to reduce the influence of noise due to head movements, we propose an optical-flow-driven method to align all frames of a micro-expression video clip. Finally, a SVM classifier with the proposed MDMO feature is adopted for micro-expression recognition. Experimental results on three spontaneous micro-expression databases, namely SMIC, CASME and CASME II, show that the MDMO can achieve better performance than two state-of-the-art baseline features, i.e., LBP-TOP and HOOF.

关键词Micro-expression optical flow recognition feature
DOI10.1109/TAFFC.2015.2485205
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(61322206 ; Beijing Natural Science Foundation(4152055) ; Open Projects Program of National Laboratory of Pattern Recognition(201306295) ; TNList Cross-discipline Foundation ; Academy of Finland ; Infotech Oulu ; 61521002 ; 61379095 ; 61375009)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号WOS:000389328800001
WOS标题词Science & Technology ; Technology
关键词[WOS]FACIAL EXPRESSIONS ; MODELS
引用统计
被引频次:19[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/20934
专题脑与认知科学国家重点实验室
作者单位1.Tsinghua Univ, Dept Comp Sci & Technol, Tsinghua Natl Lab Informat Sci & Technol, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Psychol, State Key Lab Brain & Cognit Sci, Beijing 100101, Peoples R China
3.Wenzhou Univ, Coll Teacher Educ, Wenzhou 325035, Peoples R China
4.Univ Oulu, Ctr Machine Vis Res, Infotech Oulu, POB 4500, FI-90014 Oulu, Finland
5.Univ Oulu, Dept Elect & Informat Engn, POB 4500, FI-90014 Oulu, Finland
推荐引用方式
GB/T 7714
Liu, Yong-Jin,Zhang, Jin-Kai,Yan, Wen-Jing,et al. A Main Directional Mean Optical Flow Feature for Spontaneous Micro-Expression Recognition[J]. IEEE Transactions on Affective Computing,2016,7(4):299-310.
APA Liu, Yong-Jin,Zhang, Jin-Kai,Yan, Wen-Jing,Wang, Su-Jing,Zhao, Guoying,&Fu, Xiaolan.(2016).A Main Directional Mean Optical Flow Feature for Spontaneous Micro-Expression Recognition.IEEE Transactions on Affective Computing,7(4),299-310.
MLA Liu, Yong-Jin,et al."A Main Directional Mean Optical Flow Feature for Spontaneous Micro-Expression Recognition".IEEE Transactions on Affective Computing 7.4(2016):299-310.
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