Nonverbal expressions of emotions play an important role in social interactions.
Regarding virtual environments (VEs) and the transmission of nonverbal cues in avatar-mediated
communication, knowledge of the contribution of nonverbal channels to emotion
recognition is essential. This study analyzed the impact of emotional expressions in faces and
body motion on emotion recognition. Motion capture data of expressive body movements
from actors portraying either anger or happiness were animated using avatars with congruent
and incongruent facial expressions. Participants viewed the resulting animations and rated the
perceived emotion. During stimulus presentation, gaze behavior was recorded. The analysis
of the rating results and visual attention patterns indicates that humans predominantly judge
emotions based on the facial expression and pay higher attention to the head region as an
information source to recognize emotions. This implicates that the transmission of facial
expression is of importance for the design of social VEs.
%0 Conference Paper
%1 roth2016channel
%A Roth, Daniel
%A Bloch, Carola
%A Wilbers, Anne-Kathrin
%A Latoschik, Marc Erich
%A Kaspar, Kai
%A Bente, Gary
%B Presentation at the 66th Annual Conference of the International Communication Association (ICA), June 9-13 2016, Fukuoka, Japan
%D 2016
%K droth insync myown
%T What You See is What You Get: Channel Dominance in the Decoding of Affective Nonverbal Behavior Displayed by Avatars
%U https://downloads.hci.informatik.uni-wuerzburg.de/2016-Roth-WYSIWYG.pdf
%X Nonverbal expressions of emotions play an important role in social interactions.
Regarding virtual environments (VEs) and the transmission of nonverbal cues in avatar-mediated
communication, knowledge of the contribution of nonverbal channels to emotion
recognition is essential. This study analyzed the impact of emotional expressions in faces and
body motion on emotion recognition. Motion capture data of expressive body movements
from actors portraying either anger or happiness were animated using avatars with congruent
and incongruent facial expressions. Participants viewed the resulting animations and rated the
perceived emotion. During stimulus presentation, gaze behavior was recorded. The analysis
of the rating results and visual attention patterns indicates that humans predominantly judge
emotions based on the facial expression and pay higher attention to the head region as an
information source to recognize emotions. This implicates that the transmission of facial
expression is of importance for the design of social VEs.
@inproceedings{roth2016channel,
abstract = {Nonverbal expressions of emotions play an important role in social interactions.
Regarding virtual environments (VEs) and the transmission of nonverbal cues in avatar-mediated
communication, knowledge of the contribution of nonverbal channels to emotion
recognition is essential. This study analyzed the impact of emotional expressions in faces and
body motion on emotion recognition. Motion capture data of expressive body movements
from actors portraying either anger or happiness were animated using avatars with congruent
and incongruent facial expressions. Participants viewed the resulting animations and rated the
perceived emotion. During stimulus presentation, gaze behavior was recorded. The analysis
of the rating results and visual attention patterns indicates that humans predominantly judge
emotions based on the facial expression and pay higher attention to the head region as an
information source to recognize emotions. This implicates that the transmission of facial
expression is of importance for the design of social VEs.},
added-at = {2017-10-11T12:05:19.000+0200},
author = {Roth, Daniel and Bloch, Carola and Wilbers, Anne-Kathrin and Latoschik, Marc Erich and Kaspar, Kai and Bente, Gary},
biburl = {https://www.bibsonomy.org/bibtex/20baaf8da19946ebb667ce8f420773137/hci-uwb},
booktitle = {Presentation at the 66th Annual Conference of the International Communication Association (ICA), June 9-13 2016, Fukuoka, Japan},
interhash = {929bd32e8e9a569b65d1e509ebe37069},
intrahash = {0baaf8da19946ebb667ce8f420773137},
keywords = {droth insync myown},
timestamp = {2024-05-06T17:22:37.000+0200},
title = {What You See is What You Get: Channel Dominance in the Decoding of Affective Nonverbal Behavior Displayed by Avatars},
url = {https://downloads.hci.informatik.uni-wuerzburg.de/2016-Roth-WYSIWYG.pdf},
year = 2016
}