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Micro-expression Recognition Using Dynamic Textures on Tensor Independent Color Space
Su-Jing Wang1; Wen-Jing Yan1; Xiaobai Li2; Guoying Zhao2; Xiaolan Fu1
第一作者Su-Jing Wang
2014
会议名称22nd International Conference on Pattern Recognition (ICPR)
通讯作者邮箱wangsujing@psych.ac.cn
会议录名称2014 22ND INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR)
期号不详
页码678-4683
会议日期AUG 24-28, 2014
会议地点Swedish Soc Automated Image Anal, Stockholm, SWEDEN
会议举办国SWEDEN
摘要

Micro-expression is a brief involuntary facial expression which reveals genuine emotions and helps detect lies. It intrigues psychologists and computer scientists' (especially on computer vision and pattern recognition) interests due to its promising applications in various fields. Recent research reveals that color may provide useful information for expression recognition. In this paper, we propose a novel color space model, Tensor Independent Color Space (TICS), for enhancing the performance of micro-expression recognition. An 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 in the independent color components can get higher accuracy than that in RGB. In addition, we define a set of Regions of Interest (ROIs) based on Facial Action Coding System (FACS) and calculated the dynamic texture histograms for each ROI. The experiments are conducted on two micro-expression databases, CASME and CASME 2, and the results show that the performance in TICS is better than that in RGB or gray.

DOI10.1109/ICPR.2014.800
语种英语
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被引频次:19[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.psych.ac.cn/handle/311026/26518
专题脑与认知科学国家重点实验室
作者单位1.State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences
2.Department of Computer Science and Engineering, University of Oulu
推荐引用方式
GB/T 7714
Su-Jing Wang,Wen-Jing Yan,Xiaobai Li,et al. Micro-expression Recognition Using Dynamic Textures on Tensor Independent Color Space[C],2014:678-4683.
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