Detection of Genuine and Posed Facial Expressions of Emotion: A Review
It addresses the problem of credibility assessment in facial expressions for applications in human-computer interaction and social analysis, but is incremental as it is a review paper.
This paper reviews research on distinguishing genuine from posed facial expressions, summarizing databases and computer vision methods for detection, and discussing factors affecting performance and open challenges.
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.