CAS(ME)(2): A Database for Spontaneous Macro-Expression and Micro-Expression Spotting and Recognition

doi:10.1109/TAFFC.2017.2654440

	CAS(ME)(2): A Database for Spontaneous Macro-Expression and Micro-Expression Spotting and Recognition
	Qu,Fangbing 1,2,3; Wang,Su-Jing 4; Yan,Wen-Jing 5; Li,He 1,2; Wu,Shuhang 6; Fu,Xiaolan1,2
第一作者	Qu, Fangbing ; Wang, Su-Jing
通讯作者邮箱	[email protected]
心理所单位排序	1
摘要	Deception is a very common phenomenon and its detection can be beneficial to our daily lives. Compared with other deception cues, micro-expression has shown great potential as a promising cue for deception detection. The spotting and recognition of micro-expression from long videos may significantly aid both law enforcement officers and researchers. However, database that contains both micro-expression and macro-expression in long videos is still not publicly available. To facilitate development in this field, we present a new database, Chinese Academy of Sciences Macro-Expressions and Micro-Expressions (CAS(ME)(2)), which provides both macro-expressions and micro-expressions in two parts (A and B). Part A contains 87 long videos that contain spontaneous macro-expressions and micro-expressions. Part B includes 300 cropped spontaneous macro-expression samples and 57 micro-expression samples. The emotion labels are based on a combination of action units (AUs), self-reported emotion for every facial movement, and the emotion types of emotion-evoking videos. Local Binary Pattern (LBP) was employed for the spotting and recognition of macro-expressions and micro-expressions and the results were reported as a baseline evaluation. The CAS(ME)(2) database offers both long videos and cropped expression samples, which may aid researchers in developing efficient algorithms for the spotting and recognition of macro-expressions and micro-expressions.
关键词	Macro-expression and micro-expression spotting macro-expression and micro-expression recognition micro-expression database facial action coding system
	2018-10-01
语种	英语
DOI	10.1109/TAFFC.2017.2654440
发表期刊	IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
ISSN	1949-3045
卷号	9 期号:4 页码:424-436
URL	查看原文
收录类别	SCI
资助项目	Beijing Natural Science Foundation[4152055] ; National Natural Science Foundation of China[31500875] ; National Natural Science Foundation of China[61379095] ; National Natural Science Foundation of China[61375009]
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS关键词	MODELS
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:000451918200003
WOS分区	Q1
取样对象	人类
性别	男 ; 女
年龄组	青年（18岁-29岁）
被试数量	22
测试或任务	emotion-eliciting paradigm; macro-expression and micro-expression recognition; macro-expression and micro-expression spotting
因变量指标	Action units (AUs); emotion labels; recognition performance
实验仪器	Logitech Pro C920 camera
统计方法	support vector machine (SVM); Local Binary Pattern (LBP)
引用统计	被引频次：60[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/311026/27838
专题	中国科学院行为科学重点实验室
作者单位	1.Chinese Acad Sci, Inst Psychol, State Key Lab Brain & Cognit Sci, Beijing 100101, Peoples R China; 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 3.Capital Normal Univ, Coll Presch Educ, Beijing 100048, Peoples R China; 4.Inst Psychol, CAS Key Lab Behav Sci, Beijing 100101, Peoples R China; 5.Wenzhou Univ, Coll Teacher Educ, Wenzhou 325035, Peoples R China; 6.Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110004, Liaoning, Peoples R China
第一作者单位	脑与认知科学国家重点实验室
推荐引用方式 GB/T 7714	Qu,Fangbing,Wang,Su-Jing,Yan,Wen-Jing,et al. CAS(ME)(2): A Database for Spontaneous Macro-Expression and Micro-Expression Spotting and Recognition[J]. IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,2018,9(4):424-436.
APA	Qu,Fangbing,Wang,Su-Jing,Yan,Wen-Jing,Li,He,Wu,Shuhang,&Fu,Xiaolan.(2018).CAS(ME)(2): A Database for Spontaneous Macro-Expression and Micro-Expression Spotting and Recognition.IEEE TRANSACTIONS ON AFFECTIVE COMPUTING,9(4),424-436.
MLA	Qu,Fangbing,et al."CAS(ME)(2): A Database for Spontaneous Macro-Expression and Micro-Expression Spotting and Recognition".IEEE TRANSACTIONS ON AFFECTIVE COMPUTING 9.4(2018):424-436.

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文件名称/大小	文献类型	版本类型	开放类型	使用许可
CAS(ME)2 _ A Databas（14031KB）	期刊论文	作者接受稿	限制开放	CC BY-NC-SA	请求全文