ISSN 1671-3710
CN 11-4766/R

Advances in Psychological Science ›› 2020, Vol. 28 ›› Issue (9): 1426-1436.doi: 10.3724/SP.J.1042.2020.01426

• Conceptual Framework • Previous Articles     Next Articles

Concealed emotion analysis and recognition method

WANG Su-Jing1,2(), ZOU Bochao3,4, LIU Rui4,5, LI Zhen1,2, ZHAO Guozhen1,2, LIU Ye2,6, FU Xiaolan2,6   

  1. 1CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China
    2Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
    3National Engineering Laboratory for Public Safety Risk Perception and Control by Big Data (PSRPC), China Academy of Electronics and Information Technology, Beijing 100041, China
    4Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 100069, China
    5The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Capital Medical University, Beijing 100088, China
    6State Key Laboratory of Brain and Cognitive Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2020-03-02 Online:2020-09-15 Published:2020-07-24
  • Contact: WANG Su-Jing


It is of great value to recognize concealed emotions for early warning of public security issues. Micro-expression is a vital channel to reveal concealed emotions. However, there are relatively few studies on concealed emotions, and micro-expressions are challenging to recognize because of their subtle magnitude and short duration. Existing Laboratory studies of micro-expression have few practical applications. Therefore, the perception and expression of concealed emotion should be systematically investigated by collecting micro-expression samples in an ecological situation, while synchronically collecting EEG signals for better labeling of micro-expressions. We spot and recognize concealed emotions mainly through micro-expressions, accompanied by face color analysis, gaze estimation, and contactless physiological signals measurement. Then, we verify and modify our system and method in two realistic public security related application scenarios: a Recognition Assistant System for the aggressive and suicidal behaviors of psychiatric patients and a Concealed Emotion Detection System for prisoners interview.

Key words: pattern recognition, micro-expression spotting and recognition, concealed emotion, deep learning, color space

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