ISSN 1671-3710
CN 11-4766/R
主办:中国科学院心理研究所
出版:科学出版社

心理科学进展 ›› 2010, Vol. 18 ›› Issue (9): 1359-1368.

• •    下一篇

微表情研究及其应用

吴奇;申寻兵;傅小兰   

  1. (1中国科学院心理研究所; 脑与认知国家重点实验室, 北京 100101) (2中国科学院研究生院, 北京 100049)
  • 收稿日期:2010-03-31 修回日期:1900-01-01 出版日期:2010-09-15 发布日期:2010-09-15
  • 通讯作者: 傅小兰

Micro-expression and Its Applications

WU Qi;SHENG Xun-Bing;FU Xiao-Lan   

  1. (1Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China)
    (2Graduate School of the Chinese Academy of Sciences, Beijing, 100049, China)
  • Received:2010-03-31 Revised:1900-01-01 Online:2010-09-15 Published:2010-09-15
  • Contact: FU Xiao-Lan

摘要: 微表情是一种持续时间仅为1/25秒至1/5秒的非常快速的表情, 表达了人试图压抑与隐藏的真正情感。本文系统梳理已公开发表的微表情实证研究报告, 对注重于测量微表情识别能力的早期研究、目前基于微表情训练工具(METT)的微表情识别应用研究以及刚刚萌芽的微表情表达研究进行总结分析, 明确指出以往研究中存在的问题, 建议未来研究应探讨METT在不同文化中的有效性, 研究微表情表达的基本特点和主要影响因素, 并注重发展自动化的微表情识别工具。本文提出, 基于微表情的自动谎言识别系统将是微表情研究未来的应用方向之一。

关键词: 微表情, 撒谎, 微表情识别, 微表情表达

Abstract: When an emotion is concealed or repressed, the true emotion may be manifest as a micro-expression, a fleeting facial expression discordant with the expressed emotion, usually suppressed within 1/25 to 1/5 of a second, and closely related to the deception. This article is a review of all the studies reported about micro-expression. Earlier researchers focused on the measurement of abilities to recognize micro-expression. Because of the development of measurement tools, a large number of micro-expression recognition studies emerged within the clinical domain. However, only one published empirical study has explored the generation of micro-expression, and many questions are left unanswered. Further research should focus on the cross-culture validity of Micro-Expression Training Tool (METT), the generation of micro-expression, and the development of automatic micro-expression recognition tools. Micro-expression studies can provide important insights into the development of an automatic deception detection system.

Key words: micro-expression, deception, micro-expression recognition, micro-expression generation