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

被引:196
作者
Qu, Fangbing [1 ,2 ,3 ]
Wang, Su-Jing [4 ]
Yan, Wen-Jing [5 ]
Li, He [1 ,2 ]
Wu, Shuhang [6 ]
Fu, Xiaolan [1 ,2 ]
机构
[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
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Macro-expression and micro-expression spotting; macro-expression and micro-expression recognition; micro-expression database; facial action coding system; MODELS;
D O I
10.1109/TAFFC.2017.2654440
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
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.
引用
收藏
页码:424 / 436
页数:13
相关论文
共 52 条
[1]  
[Anonymous], 2016, PROC INT C HUM COMPU
[2]  
[Anonymous], 2009, INT C IMAGING CRIME, DOI DOI 10.1049/IC.2009.0244
[3]  
[Anonymous], USING ACTOR PORTRAYA
[4]  
[Anonymous], 2009, TELLING LIES CLUES D
[5]  
[Anonymous], 2011, International Journal of Wavelets Multiresolution and Information Processing, DOI DOI 10.1142/S021969130400041X
[6]   Robust Discriminative Response Map Fitting with Constrained Local Models [J].
Asthana, Akshay ;
Zafeiriou, Stefanos ;
Cheng, Shiyang ;
Pantic, Maja .
2013 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2013, :3444-3451
[7]  
Bartlett M. S., 2006, Journal of Multimedia, V1, DOI 10.4304/jmm.1.6.22-35
[8]   Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications [J].
Calvo, Rafael A. ;
D'Mello, Sidney .
IEEE TRANSACTIONS ON AFFECTIVE COMPUTING, 2010, 1 (01) :18-37
[9]   ACTIVE SHAPE MODELS - THEIR TRAINING AND APPLICATION [J].
COOTES, TF ;
TAYLOR, CJ ;
COOPER, DH ;
GRAHAM, J .
COMPUTER VISION AND IMAGE UNDERSTANDING, 1995, 61 (01) :38-59
[10]   Beyond emotion archetypes: Databases for emotion modelling using neural networks [J].
Cowie, R ;
Douglas-Cowie, E ;
Cox, C .
NEURAL NETWORKS, 2005, 18 (04) :371-388