CASME II: An Improved Spontaneous Micro-Expression Database and the Baseline Evaluation |
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| Authors: | Wen-Jing Yan Xiaobai Li Su-Jing Wang Guoying Zhao Yong-Jin Liu Yu-Hsin Chen Xiaolan Fu |
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| Institution: | 1. State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.; 2. University of Chinese Academy of Sciences, Beijing, China.; 3. Center for Machine Vision Research, Department of Computer Science and Engineering, University of Oulu, Oulu, Finland.; 4. TNList, Department of Computer Science and Technology, Tsinghua University, Beijing, China.; University of Lincoln, United Kingdom, |
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| Abstract: | 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. |
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