%0 Journal Article %1 roth:2015b %A Roth, Daniel %A Bloch, Carola %A Wilbers, Anne-Kathrin %A Kaspar, Kai %A Latoschik, Marc Erich %A Bente, Gary %B Abstracts of the 18th European Conference on Eye Movements %D 2015 %E Ansorge, U. %E Ditye, T. %E Florack, A. %E Leder, H. %J Journal of Eye Movement Research %K droth insync myown %N 4 %P 192 %T Quantification of Signal Carriers for Emotion Recognition from Body Movement and Facial Affects %U http://www.hci.uni-wuerzburg.de/download/2015-ecem-roth-quantification-signal-carriers.pdf %V 8 %X Nonverbal expressions of emotions in the human face and body play an important role in social interactions. Regarding affective human-computer interfaces and the use of nonver- bal cues in computer-mediated communication, knowledge about the contribution of differ- ent nonverbal channels to emotion recognition is essential. The current study analyzed the relative impact of emotional expressions in faces and bodies of avatars on visual attention and emotion recognition. Avatar animations of expressive body movements were based on motion capture data from actors portraying either anger or happiness. A pre study was conducted to select expressions which were either perceived as anger, happiness or neu- tral. We systematically combined facial expressions and expressive movements by using blend shapes for facial animation resulting in congruent and incongruent face-body com- binations. 68 participants watched the resulting videos and rated the perceived emotion. During stimulus presentation gaze behavior was recorded with a SMI RED500 eye tracker. Using dynamic regions of interest we calculated dwell times and number of fixations in the face, head and body region. Results indicate that humans prioritize the face and head region as an information source emotion recognition. This priority is visible in the visual attention patterns as well as in the explained judgment variance.

@article{roth:2015b, abstract = {Nonverbal expressions of emotions in the human face and body play an important role in social interactions. Regarding affective human-computer interfaces and the use of nonver- bal cues in computer-mediated communication, knowledge about the contribution of differ- ent nonverbal channels to emotion recognition is essential. The current study analyzed the relative impact of emotional expressions in faces and bodies of avatars on visual attention and emotion recognition. Avatar animations of expressive body movements were based on motion capture data from actors portraying either anger or happiness. A pre study was conducted to select expressions which were either perceived as anger, happiness or neu- tral. We systematically combined facial expressions and expressive movements by using blend shapes for facial animation resulting in congruent and incongruent face-body com- binations. 68 participants watched the resulting videos and rated the perceived emotion. During stimulus presentation gaze behavior was recorded with a SMI RED500 eye tracker. Using dynamic regions of interest we calculated dwell times and number of fixations in the face, head and body region. Results indicate that humans prioritize the face and head region as an information source emotion recognition. This priority is visible in the visual attention patterns as well as in the explained judgment variance.}, added-at = {2018-03-09T16:05:00.000+0100}, author = {Roth, Daniel and Bloch, Carola and Wilbers, Anne-Kathrin and Kaspar, Kai and Latoschik, Marc Erich and Bente, Gary}, biburl = {https://www.bibsonomy.org/bibtex/27a383240816d5895f7c296ffc0a5ad21/rothnroll}, booktitle = {Abstracts of the 18th European Conference on Eye Movements}, date-added = {2015-08-31 05:37:13 +0000}, date-modified = {2015-08-31 05:47:50 +0000}, editor = {Ansorge, U. and Ditye, T. and Florack, A. and Leder, H.}, interhash = {acf854def1b00c8c59208f3c95a4a50d}, intrahash = {7a383240816d5895f7c296ffc0a5ad21}, journal = {Journal of Eye Movement Research}, keywords = {droth insync myown}, number = 4, pages = 192, timestamp = {2018-03-09T16:05:00.000+0100}, title = {Quantification of Signal Carriers for Emotion Recognition from Body Movement and Facial Affects}, url = {http://www.hci.uni-wuerzburg.de/download/2015-ecem-roth-quantification-signal-carriers.pdf}, volume = 8, year = 2015 }