Recognition profile of emotions in natural and virtual faces.

BACKGROUND: Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural em...

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Main Authors: Miriam Dyck, Maren Winbeck, Susanne Leiberg, Yuhan Chen, Ruben C Gur, Klaus Mathiak
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2008-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC2574410?pdf=render
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spelling doaj-7c7208ccb4424cbeae370093b57a700e2020-11-25T02:22:09ZengPublic Library of Science (PLoS)PLoS ONE1932-62032008-01-01311e362810.1371/journal.pone.0003628Recognition profile of emotions in natural and virtual faces.Miriam DyckMaren WinbeckSusanne LeibergYuhan ChenRuben C GurKlaus MathiakBACKGROUND: Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups. METHODOLOGY/PRINCIPAL FINDINGS: Thirty-two healthy volunteers between the age of 20 and 60 rated pictures of natural human faces and faces of virtual characters (avatars) with respect to the expressed emotions: happiness, sadness, anger, fear, disgust, and neutral. Results indicate that virtual emotions were recognized comparable to natural ones. Recognition differences in virtual and natural faces depended on specific emotions: whereas disgust was difficult to convey with the current avatar technology, virtual sadness and fear achieved better recognition results than natural faces. Furthermore, emotion recognition rates decreased for virtual but not natural faces in participants over the age of 40. This specific age effect suggests that media exposure has an influence on emotion recognition. CONCLUSIONS/SIGNIFICANCE: Virtual and natural facial displays of emotion may be equally effective. Improved technology (e.g. better modelling of the naso-labial area) may lead to even better results as compared to trained actors. Due to the ease with which virtual human faces can be animated and manipulated, validated artificial emotional expressions will be of major relevance in future research and therapeutic applications.http://europepmc.org/articles/PMC2574410?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Miriam Dyck
Maren Winbeck
Susanne Leiberg
Yuhan Chen
Ruben C Gur
Klaus Mathiak
spellingShingle Miriam Dyck
Maren Winbeck
Susanne Leiberg
Yuhan Chen
Ruben C Gur
Klaus Mathiak
Recognition profile of emotions in natural and virtual faces.
PLoS ONE
author_facet Miriam Dyck
Maren Winbeck
Susanne Leiberg
Yuhan Chen
Ruben C Gur
Klaus Mathiak
author_sort Miriam Dyck
title Recognition profile of emotions in natural and virtual faces.
title_short Recognition profile of emotions in natural and virtual faces.
title_full Recognition profile of emotions in natural and virtual faces.
title_fullStr Recognition profile of emotions in natural and virtual faces.
title_full_unstemmed Recognition profile of emotions in natural and virtual faces.
title_sort recognition profile of emotions in natural and virtual faces.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2008-01-01
description BACKGROUND: Computer-generated virtual faces become increasingly realistic including the simulation of emotional expressions. These faces can be used as well-controlled, realistic and dynamic stimuli in emotion research. However, the validity of virtual facial expressions in comparison to natural emotion displays still needs to be shown for the different emotions and different age groups. METHODOLOGY/PRINCIPAL FINDINGS: Thirty-two healthy volunteers between the age of 20 and 60 rated pictures of natural human faces and faces of virtual characters (avatars) with respect to the expressed emotions: happiness, sadness, anger, fear, disgust, and neutral. Results indicate that virtual emotions were recognized comparable to natural ones. Recognition differences in virtual and natural faces depended on specific emotions: whereas disgust was difficult to convey with the current avatar technology, virtual sadness and fear achieved better recognition results than natural faces. Furthermore, emotion recognition rates decreased for virtual but not natural faces in participants over the age of 40. This specific age effect suggests that media exposure has an influence on emotion recognition. CONCLUSIONS/SIGNIFICANCE: Virtual and natural facial displays of emotion may be equally effective. Improved technology (e.g. better modelling of the naso-labial area) may lead to even better results as compared to trained actors. Due to the ease with which virtual human faces can be animated and manipulated, validated artificial emotional expressions will be of major relevance in future research and therapeutic applications.
url http://europepmc.org/articles/PMC2574410?pdf=render
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