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FACSGen 2.0 animation software: Generating 3D FACS-valid facial expressions for emotion research

Krumhuber, E; Tamarit, L; Roesch, EB; Scherer, KR; (2012) FACSGen 2.0 animation software: Generating 3D FACS-valid facial expressions for emotion research. Emotion , 12 (2) pp. 351-363. 10.1037/a0026632. Green open access

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Abstract

In this article, we present FACSGen 2.0, new animation software for creating static and dynamic three-dimensional facial expressions on the basis of the Facial Action Coding System (FACS). FACSGen permits total control over the action units (AUs), which can be animated at all levels of intensity and applied alone or in combination to an infinite number of faces. In two studies, we tested the validity of the software for the AU appearance defined in the FACS manual and the conveyed emotionality of FACSGen expressions. In Experiment 1, four FACS-certified coders evaluated the complete set of 35 single AUs and 54 AU combinations for AU presence or absence, appearance quality, intensity, and asymmetry. In Experiment 2, lay participants performed a recognition task on emotional expressions created with FACSGen software and rated the similarity of expressions displayed by human and FACSGen faces. Results showed good to excellent classification levels for all AUs by the four FACS coders, suggesting that the AUs are valid exemplars of FACS specifications. Lay participants' recognition rates for nine emotions were high, and comparisons of human and FACSGen expressions were very similar. The findings demonstrate the effectiveness of the software in producing reliable and emotionally valid expressions, and suggest its application in numerous scientific areas, including perception, emotion, and clinical and neuroscience research.

Type: Article
Title: FACSGen 2.0 animation software: Generating 3D FACS-valid facial expressions for emotion research
Open access status: An open access version is available from UCL Discovery
DOI: 10.1037/a0026632
Publisher version: http://dx.doi.org/10.1037/a0026632
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: emotion, facial expression, Facial Action Coding System, FACSGen, animation
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: https://discovery.ucl.ac.uk/id/eprint/1400671
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