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CAS(ME)(2): A Database for Spontaneous Macro-Expression and Micro-Expression Spotting and Recognition
Qu, Fangbing1,2,3; Wang, Su-Jing4; Yan, Wen-Jing5; Li, He1,2; Wu, Shuhang6; Fu, Xiaolan1,2
Corresponding AuthorFu, Xiaolan(fuxl@psych.ac.cn)
2018-10-01
Source PublicationIEEE TRANSACTIONS ON AFFECTIVE COMPUTING
ISSN1949-3045
Volume9Issue:4Pages:424-436
AbstractDeception 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.
KeywordMacro-expression and micro-expression spotting macro-expression and micro-expression recognition micro-expression database facial action coding system
DOI10.1109/TAFFC.2017.2654440
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China ; Beijing Natural Science Foundation
Funding ProjectBeijing 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] ; National Natural Science Foundation of China[61375009] ; National Natural Science Foundation of China[61379095] ; National Natural Science Foundation of China[31500875] ; Beijing Natural Science Foundation[4152055]
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000451918200003
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS KeywordMODELS
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/27838
Collection中国科学院行为科学重点实验室
Corresponding AuthorFu, Xiaolan
Affiliation1.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
Recommended Citation
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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