Detection of Genuine and Posed Facial Expressions of Emotion: Databases and Methods

Frontiers in Psychology

article

Shan Jia¹  Shuo Wang³  Chuanbo Hu²  Paula J. Webster³  Xin Li² 

[1] State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University;Lane Department of Computer Science and Electrical Engineering, West Virginia University, United States;Department of Chemical and Biomedical Engineering, West Virginia University, United States

关键词: facial expressions analysis;    spontaneous expression;    posed expression;    expressions classification;    countermeasure;   

DOI  :  10.3389/fpsyg.2020.580287

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Facial expressions of emotion play an important role in human social interactions. However, posed expressions of emotion are not always the same as genuine feelings. Recent research has found that facial expressions are increasingly used as a tool for understanding social interactions instead of personal emotions. Therefore, the credibility assessment of facial expressions, namely, the discrimination of genuine (spontaneous) expressions from posed (deliberate/volitional/deceptive) ones, is a crucial yet challenging task in facial expression understanding. With recent advances in computer vision and machine learning techniques, rapid progress has been made in recent years for automatic detection of genuine and posed facial expressions. This paper presents a general review of the relevant research, including several spontaneous vs. posed (SVP) facial expression databases and various computer vision based detection methods. In addition, a variety of factors that will influence the performance of SVP detection methods are discussed along with open issues and technical challenges in this nascent field.

【 授权许可】

CC BY