Emotional Human-Machine Interaction: Cues from Facial Expressions
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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Emotional Human-Machine Interaction : Cues from Facial Expressions. / Tews, Tessa-Karina; Oehl, Michael; Siebert, Felix et al.
Human Interface and the Management of Information: Interacting with Information: Symposium on Human Interface 2011, Held as a Part of HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part I. Hrsg. / Michael J. Smith; Gavriel Salvendy. Berlin, Heidelberg : Springer, 2011. S. 641-650 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 6771 LNCS, Nr. PART 1).Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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RIS
TY - CHAP
T1 - Emotional Human-Machine Interaction
T2 - 14th International Conference on Human-Computer Interaction - HCI International 2011
AU - Tews, Tessa-Karina
AU - Oehl, Michael
AU - Siebert, Felix
AU - Höger, Rainer
AU - Faasch, Helmut
N1 - Conference code: 14
PY - 2011
Y1 - 2011
N2 - Emotion detection provides a promising basis for designing future-oriented human centered design of Human-Machine Interfaces. Affective Computing can facilitate human-machine communication. Such adaptive advanced driver assistance systems (ADAS) which are dependent on the emotional state of the driver can be applied in cars. In contrast to the majority of former studies that only used static recognition methods, we investigated a new dynamic approach for detecting emotions in facial expressions in an artificial setting and in a driving context. By analyzing the changes of an area defined by a number of dots that were arranged on participants' faces, variables were extracted to classify the participants' emotions according to the Facial Action Coding System. The results of our novel way to categorize emotions lead to a discussion on additional applications and limitations that frames an attempted approach of emotion detection in cars. Implications for further research and applications are outlined.
AB - Emotion detection provides a promising basis for designing future-oriented human centered design of Human-Machine Interfaces. Affective Computing can facilitate human-machine communication. Such adaptive advanced driver assistance systems (ADAS) which are dependent on the emotional state of the driver can be applied in cars. In contrast to the majority of former studies that only used static recognition methods, we investigated a new dynamic approach for detecting emotions in facial expressions in an artificial setting and in a driving context. By analyzing the changes of an area defined by a number of dots that were arranged on participants' faces, variables were extracted to classify the participants' emotions according to the Facial Action Coding System. The results of our novel way to categorize emotions lead to a discussion on additional applications and limitations that frames an attempted approach of emotion detection in cars. Implications for further research and applications are outlined.
KW - Business psychology
KW - Emotion detection
KW - human-computer interaction
KW - human-centered design
KW - affective computing
KW - affective computing
KW - Emotion detection
KW - human-centered design
KW - human-computer interaction
UR - http://www.scopus.com/inward/record.url?scp=79960302127&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21793-7_73
DO - 10.1007/978-3-642-21793-7_73
M3 - Article in conference proceedings
SN - 978-3-642-21792-0
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 641
EP - 650
BT - Human Interface and the Management of Information: Interacting with Information
A2 - Smith, Michael J.
A2 - Salvendy, Gavriel
PB - Springer
CY - Berlin, Heidelberg
Y2 - 9 July 2011 through 14 July 2011
ER -