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隐藏情绪分析与识别方法

本站小编 Free考研考试/2022-01-01

王甦菁1,2(), 邹博超3,4, 刘瑞4,5, 李振1,2, 赵国朕1,2, 刘烨2,6, 傅小兰2,6
1中国科学院行为科学重点实验室(中国科学院心理研究所), 北京 100101
2中国科学院大学心理学系, 北京 100039
3中国电子科学研究院, 社会安全风险感知与防控大数据应用国家工程实验室, 北京 100041
4首都医科大学,人脑保护高精尖创新中心, 北京 100069
5首都医科大学附属北京安定医院, 国家精神心理疾病临床医学研究中心, 精神疾病诊断与治疗北京市重点实验室, 北京 100088
6中国科学院心理研究所脑与认知科学国家重点实验室, 北京 100039
收稿日期:2020-03-02出版日期:2020-09-15发布日期:2020-07-24
通讯作者:王甦菁E-mail:wangsujing@psych.ac.cn

基金资助:* 国家自然科学基金项目(U19B2032);国家自然科学基金项目(61772511);社会安全风险感知与防控大数据应用国家工程实验室主任基金项目(18112403)

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
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:2020-03-02Online:2020-09-15Published:2020-07-24
Contact:WANG Su-Jing E-mail:wangsujing@psych.ac.cn






摘要/Abstract


摘要: 隐藏情绪识别对公共安全防范与预警具有重要的意义。微表情是揭示隐藏情绪的一条重要通道。但目前隐藏情绪研究较少且微表情因其细微幅度与快速出现等特性难以识别, 其研究尚未在实际中广泛应用。因为, 隐藏情绪的认知与表达机理亟需系统的研究,采集实际场景中的微表情数据, 并以脑电信号辅助微表情的精确标注是提高微表情标注效率的有效途径。深入研究微表情识别方法, 并辅以人脸颜色、注视估计和非接触生理信号等多通道数据, 以检测与识别隐藏情绪。社会公共安全是隐藏情绪分析和识别的典型场景。面向精神疾病患者两害行为(即危害自身或他人的危险行为)风险评估和服刑人员会见场景隐藏情绪检测, 可以有效地对相应系统和方法进行验证和修正。



图1研究路线图
图1研究路线图







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