Micro-Expression Recognition Using Color Spaces

doi:10.1109/TIP.2015.2496314

	Micro-Expression Recognition Using Color Spaces
	Wang,Su-Jing 1,2; Yan,Wen-Jing 3; Li,Xiaobai 4; Zhao,Guoying 4; Zhou,Chun-Guang 2,5; Fu,Xiaolan6 ; Yang,Minghao 7; Tao,Jianhua 7
第一作者	Wang, Su-Jing
通讯作者邮箱	wangsujing@psych.ac.cn
心理所单位排序	1
摘要	Micro-expressions are brief involuntary facial expressions that reveal genuine emotions and, thus, help detect lies. Because of their many promising applications, they have attracted the attention of researchers from various fields. Recent research reveals that two perceptual color spaces (CIELab and CIELuv) provide useful information for expression recognition. This paper is an extended version of our International Conference on Pattern Recognition paper, in which we propose a novel color space model, tensor independent color space (TICS), to help recognize micro-expressions. In this paper, we further show that CIELab and CIELuv are also helpful in recognizing micro-expressions, and we indicate why these three color spaces achieve better performance. A micro-expression color video clip is treated as a fourth-order tensor, i.e., a four-dimension array. The first two dimensions are the spatial information, the third is the temporal information, and the fourth is the color information. We transform the fourth dimension from RGB into TICS, in which the color components are as independent as possible. The combination of dynamic texture and independent color components achieves a higher accuracy than does that of RGB. In addition, we define a set of regions of interests (ROIs) based on the facial action coding system and calculated the dynamic texture histograms for each ROI. Experiments are conducted on two micro-expression databases, CASME and CASME 2, and the results show that the performances for TICS, CIELab, and CIELuv are better than those for RGB or gray.
关键词	Micro-expression recognition color spaces tensor analysis local binary patterns facial action coding system
	2015-12-01
语种	英语
DOI	10.1109/TIP.2015.2496314
发表期刊	IEEE TRANSACTIONS ON IMAGE PROCESSING
ISSN	1057-7149
卷号	24 期号:12 页码:6034-6047
期刊论文类型	Article
URL	查看原文
收录类别	SCI
WOS关键词	LOCAL BINARY PATTERNS ; FACE RECOGNITION ; TEXTURE ; CLASSIFICATION ; MODELS
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000364992700004
WOS分区	Q1
Q分类	Q1
测试或任务	micro-expression recognition; Tensor Independent Color Space (TICS)
因变量指标	recognition performances
引用统计	被引频次：131[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.psych.ac.cn/handle/311026/15340
专题	脑与认知科学国家重点实验室
作者单位	1.Chinese Acad Sci, Inst Psychol, Key Lab Behav Sci, Beijing 100101, Peoples R China; 2.Jilin Univ, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun 130012, Peoples R China; 3.Wenzhou Univ, Coll Teacher Educ, Wenzhou 325035, Peoples R China; 4.Univ Oulu, Dept Comp Sci & Engn, FI-90014 Oulu, Finland; 5.Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China; 6.Chinese Acad Sci, Inst Psychol, State Key Lab Brain & Cognit Sci, Beijing 100101, Peoples R China; 7.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
第一作者单位	中国科学院行为科学重点实验室
推荐引用方式 GB/T 7714	Wang,Su-Jing,Yan,Wen-Jing,Li,Xiaobai,et al. Micro-Expression Recognition Using Color Spaces[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2015,24(12):6034-6047.
APA	Wang,Su-Jing.,Yan,Wen-Jing.,Li,Xiaobai.,Zhao,Guoying.,Zhou,Chun-Guang.,...&Tao,Jianhua.(2015).Micro-Expression Recognition Using Color Spaces.IEEE TRANSACTIONS ON IMAGE PROCESSING,24(12),6034-6047.
MLA	Wang,Su-Jing,et al."Micro-Expression Recognition Using Color Spaces".IEEE TRANSACTIONS ON IMAGE PROCESSING 24.12(2015):6034-6047.

条目包含的文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
WOS_000364992700004.（20175KB）	期刊论文	出版稿	暂不开放	CC BY-NC-SA	请求全文