PDF(Pubmed)
Abstract：
Micro-expressions (ME) are rapidly occurring expressions that reveal the true emotions that a human being is trying to hide, cover, or suppress. These expressions, which reveal a person\'s actual feelings, have a broad spectrum of applications in public safety and clinical diagnosis. This study provides a comprehensive review of the area of ME recognition. A bibliometric and network analysis techniques is used to compile all the available literature related to ME recognition. A total of 735 publications from the Web of Science (WOS) and Scopus databases were evaluated from December 2012 to December 2022 using all relevant keywords. The first round of data screening produced some basic information, which was further extracted for citation, coupling, co-authorship, co-occurrence, bibliographic, and co-citation analysis. Additionally, a thematic and descriptive analysis was executed to investigate the content of prior research findings, and research techniques used in the literature. The year wise publications indicated that the published literature between 2012 and 2017 was relatively low but however by 2021, a nearly 24-fold increment made it to 154 publications. The three topmost productive journals and conferences included IEEE Transactions on Affective Computing (n = 20 publications) followed by Neurocomputing (n = 17) and Multimedia tools and applications (n = 15). Zhao G was the most proficient author with 48 publications and the top influential country was China (620 publications). Publications by citations showed that each of the authors acquired citations ranging from 100 to 1225. While publications by organizations indicated that the University of Oulu had the most published papers (n = 51). Deep learning, facial expression recognition, and emotion recognition were among the most frequently used terms. It has been discovered that ME research was primarily classified in the discipline of engineering, with more contribution from China and Malaysia comparatively.
摘要：
微表情（ME）是快速发生的表情，揭示了人类试图隐藏的真实情感，封面,或压制。这些表达，它揭示了一个人的真实感受，在公共安全和临床诊断中有广泛的应用。这项研究提供了对ME识别领域的全面回顾。使用文献计量和网络分析技术来编译与ME识别相关的所有可用文献。从2012年12月到2022年12月，使用所有相关关键字对来自WebofScience（WOS）和Scopus数据库的735种出版物进行了评估。第一轮数据筛选产生了一些基本信息,被进一步提取用于引用，耦合器,合著者,共现,书目,和共同引用分析。此外,进行了专题和描述性分析，以调查先前研究结果的内容，和文献中使用的研究技术。年度明智的出版物表明，2012年至2017年之间的已发表文献相对较低，但到2021年，近24倍的增长使其达到154种出版物。三个最富有成效的期刊和会议包括IEEE情感计算交易（n=20出版物），其次是神经计算（n=17）和多媒体工具和应用程序（n=15）。赵G是最熟练的作家，拥有48种出版物，影响力最大的国家是中国（620种出版物）。引用的出版物表明，每位作者都获得了100到1225的引用。虽然组织的出版物表明奥卢大学发表的论文最多（n=51）。深度学习,面部表情识别,情感识别是最常用的术语之一。已经发现，ME研究主要被归类在工程学科中，中国和马来西亚的贡献相对较多。
