For micro-expression recognition: Database and suggestions
For micro-expression recognition: Database and suggestions
复制标题
微表情识别：数据库和建议
DOI：
10.1016/j.neucom.2014.01.029
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发表时间：
2014-07-20
期刊：
影响因子：
6
通讯作者：
Fu, Xiaolan
中科院分区：
文献类型：
--
作者：
Yan, Wen-Jing;Wang, Su-Jing;Fu, Xiaolan
无论是在科学领域还是在大众媒体，微表情都越来越受到关注。它代表了人们试图隐藏的真实情感，因此使其成为测谎的一个有希望的线索。由于微表情被认为是肉眼几乎无法察觉的，研究人员试图自动检测和识别这些短暂的面部表情，以帮助人们利用这种欺骗线索。然而，缺乏完善的微表情数据库可能是最大的障碍。虽然已经建立了一些数据库，但无论是在微表达的诱导方法还是在标记方面都存在一些问题。我们建立了一个自发的微表达数据库，具有严格的框架点样，Au编码和微表达标记。本文介绍了在实验室条件下，如何诱发被试的微表情，并以心理学为指导建立微表情数据库。此外，本文提出的问题，可以帮助研究人员有效地使用微表情数据库，提高微表情识别。(C)2014爱思唯尔有限公司版权所有。
Micro-expression is gaining more attention in both the scientific field and the mass media. It represents genuine emotions that people try to conceal, thus making it a promising cue for lie detection. Since micro-expressions are considered almost imperceptible to naked eyes, researchers have sought to automatically detect and recognize these fleeting facial expressions to help people make use of such deception cues. However, the lack of well-established micro-expression databases might be the biggest obstacle. Although several databases have been developed, there may exist some problems either in the approach of eliciting micro-expression or the labeling. We built a spontaneous micro-expression database with rigorous frame spotting, AU coding and micro-expression labeling. This paper introduces how the micro-expressions were elicited in a laboratory situation and how the database was built with the guide of psychology. In addition, this paper proposes issues that may help researchers effectively use micro-expression databases and improve micro-expression recognition. (C) 2014 Elsevier B.V. All rights reserved.