Micro-Expression Recognition Using Color Spaces
文献类型：期刊论文
| 作者 | Wang, Su-Jing1,2; Yan, Wen-Jing3; Li, Xiaobai4; Zhao, Guoying4; Zhou, Chun-Guang2,5; Fu, Xiaolan6 ; Yang, Minghao7; Tao, Jianhua7; Fu,Xiaolan
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| 刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
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| 出版日期 | 2015-12-01 |
| 卷号 | 24期号:12页码:6034-6047 |
| 关键词 | Micro-expression recognition color spaces tensor analysis local binary patterns facial action coding system |
| ISSN号 | 1057-7149 |
| 英文摘要 | 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. |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000364992700004 |
| 源URL | [http://ir.psych.ac.cn/handle/311026/15340]  |
| 专题 | 心理研究所_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 |
| 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.,...&Fu,Xiaolan.(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. |
入库方式： OAI收割
来源：心理研究所
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