The effect of dynamics on identifying basic emotions from synthetic and natural faces

• Published in: International journal of human-computer studies Vol. 66; no. 4; pp. 233 - 242
• Main Authors: Kätsyri, Jari, Sams, Mikko
• Format: Journal Article
• Language: English
• Published: London Elsevier Ltd 01.04.2008; Elsevier
• Subjects: Applied sciences; Artificial intelligence; Basic emotions; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Exact sciences and technology; Facial animation; Movement perception; Pattern recognition. Digital image processing. Computational geometry; Software; EF; Basic emotions; Movement perception; TAS-20; TH; TKK; CK; FACS; Facial animation; Artificial life; Face recognition; Emotion emotionality; Personality; Computer animation; Social psychology; User interface; Animal; Facies; System identification; Dynamic model; Facial expression; Display
• ISSN: 1071-5819; 1095-9300
• DOI: 10.1016/j.ijhcs.2007.10.001

The identification of basic emotions (anger, disgust, fear, happiness, sadness and surprise) has been studied widely from pictures of facial expressions. Until recently, the role of dynamic information in identifying facial emotions has received little attention. There is evidence that dynamics improves the identification of basic emotions from synthetic (computer-animated) facial expressions [Wehrle, T., Kaiser, S., Schmidt, S., Scherer, K.R., 2000. Studying dynamic models of facial expression of emotion using synthetic animated faces. Journal of Personality and Social Psychology 78 (1), 105–119.]; however, similar result has not been confirmed with natural human faces. We compared the identification of basic emotions from both natural and synthetic dynamic vs. static facial expressions in 54 subjects. We found no significant differences in the identification of static and dynamic expressions from natural faces. In contrast, some synthetic dynamic expressions were identified much more accurately than static ones. This effect was evident only with synthetic facial expressions whose static displays were non-distinctive. Our results show that dynamics does not improve the identification of already distinctive static facial displays. On the other hand, dynamics has an important role for identifying subtle emotional expressions, particularly from computer-animated synthetic characters.