Detection of Genuine and Posed Facial Expressions of Emotion: A Review

TL;DR

This review paper discusses recent advances in automatic detection of genuine versus posed facial expressions, highlighting databases, detection methods, influencing factors, and ongoing challenges in the field.

Contribution

It provides a comprehensive overview of current research, databases, and techniques for discriminating genuine from posed facial expressions of emotion.

Findings

Several SVP facial expression databases are available.

Various computer vision methods have been developed for detection.

Performance is influenced by multiple factors and challenges remain.

Abstract

Facial expressions of emotion play an important role in human social interactions. However, posed acting is not always the same as genuine feeling. 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. 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.