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Recognition of emotion in moving and static composite faces

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Kleiner,  M
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Project group: Cognitive Engineering, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Knappmeyer,  B
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Chiller-Glaus, S., Schwaninger, A., Hofer, K., Kleiner, M., & Knappmeyer, B. (2011). Recognition of emotion in moving and static composite faces. Swiss Journal of Psychology, 70(4), 233-240. doi:10.1024/1421-0185/a000061.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-B8C8-8
Abstract
This paper investigates whether the greater accuracy of emotion identification for dynamic versus static expressions, as noted in previous research, can be explained through heightened levels of either component or configural processing. Using a paradigm by Young, Hellawell, and Hay (1987), we tested recognition performance of aligned and misaligned composite faces with six basic emotions (happiness, fear, disgust, surprise, anger, sadness). Stimuli were created using 3D computer graphics and were shown as static peak expressions (static condition) and 7 s video sequences (dynamic condition). The results revealed that, overall, moving stimuli were better recognized than static faces, although no interaction between motion and other factors was found. For happiness, sadness, and surprise, misaligned composites were better recognized than aligned composites, suggesting that aligned composites fuse to form a single expression, while the two halves of misaligned composites are perceived as two separate emotions. For anger, disgust, and fear, this was not the case. These results indicate that emotions are perceived on the basis of both configural and component-based information, with specific activation patterns for separate emotions, and that motion has a quality of its own and does not increase configural or component-based recognition separately.