CASME II: an improved spontaneous micro-expression database and the baseline evaluation.
A robust automatic micro-expression recognition system would have broad applications in national safety, police interrogation, and clinical diagnosis. Developing such a system requires high quality databases with sufficient training samples which are currently not available. We reviewed the previously developed micro-expression databases and built an improved one (CASME II), with higher temporal resolution (200 fps) and spatial resolution (about 280×340 pixels on facial area). We elicited participants' facial expressions in a well-controlled laboratory environment and proper illumination (such as removing light flickering). Among nearly 3000 facial movements, 247 micro-expressions were selected for the database with action units (AUs) and emotions labeled. For baseline evaluation, LBP-TOP and SVM were employed respectively for feature extraction and classifier with the leave-one-subject-out cross-validation method. The best performance is 63.41% for 5-class classification.
State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China ; University of Chinese Academy of Sciences, Beijing, China.
Wen-Jing
WJ
Yan
Center for Machine Vision Research, Department of Computer Science and Engineering, University of Oulu, Oulu, Finland.
Xiaobai
X
Li
State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Su-Jing
SJ
Wang
Center for Machine Vision Research, Department of Computer Science and Engineering, University of Oulu, Oulu, Finland.
Guoying
G
Zhao
TNList, Department of Computer Science and Technology, Tsinghua University, Beijing, China.
Yong-Jin
YJ
Liu
State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China ; University of Chinese Academy of Sciences, Beijing, China.
Yu-Hsin
YH
Chen
State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Xiaolan
X
Fu
D001699:Biometry / Q000379:methods*; D016208:Databases, Factual; D004644:Emotions / Q000502:physiology*; D005145:Face / Q000033:anatomy & histology / Q000502:physiology; D005149:Facial Expression; D044707:Forensic Sciences / Q000379:methods; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D060388:Support Vector Machine