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

Authors :
Fangbing Qu
He Li
Su-Jing Wang
Wen-Jing Yan
Shuhang Wu
Xiaolan Fu
Source :
IEEE Transactions on Affective Computing. 9:424-436
Publication Year :
2018
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2018.

Abstract

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.

Details

ISSN :
23719850
Volume :
9
Database :
OpenAIRE
Journal :
IEEE Transactions on Affective Computing
Accession number :
edsair.doi...........2b750a37083d227eb641f01857c34170