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

Shan Jia, Shuo Wang, Chuanbo Hu, Paula J. Webster, Xin Li

Research output: Contribution to journalReview articlepeer-review

16 Scopus citations

Abstract

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.

Original languageEnglish
Article number580287
JournalFrontiers in Psychology
Volume11
DOIs
StatePublished - Jan 15 2021

Keywords

  • countermeasure
  • expressions classification
  • facial expressions analysis
  • posed expression
  • spontaneous expression

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