TY - CHAP

T1 - Current and New Research Perspectives on Dynamic Facial Emotion Detection in Emotional Interface

AU - Tews, Tessa-Karina

AU - Oehl, Michael

AU - Faasch, Helmut

AU - Kanno, T.

N1 - Conference code: 16

PY - 2014

Y1 - 2014

N2 - In recent years there has been an increasing interdisciplinary exchange between psychology and computer science in the field of recognizing emotions for future-oriented Human-Computer and Human-Machine Interfaces. Although affective computing research has made enormous progress in automatically recognizing facial expressions, it has not yet been fully clarified how algorithms can learn to encode or decode a human face in a real environment. Consequently, our research focuses on the detection of emotions or affective states in a Human-Machine setting. In contrast to other approaches, we use a psychology driven approach trying to minimize complex computations by using a simple dot-based feature extraction method. We suggest a new approach within, but not limited to, a Human-Machine Interface context which detects emotions by analyzing the dynamic change in facial expressions. In order to compare our approach, we discuss our software with respect to other developed facial expression studies in context of its application in a chat environment. Our approach indicates promising results that the program could accurately detect emotions. Implications for further research as well as for applied issues in many areas of Human-Computer Interaction, particularly for affective and social computing, will be discussed and outlined.

AB - In recent years there has been an increasing interdisciplinary exchange between psychology and computer science in the field of recognizing emotions for future-oriented Human-Computer and Human-Machine Interfaces. Although affective computing research has made enormous progress in automatically recognizing facial expressions, it has not yet been fully clarified how algorithms can learn to encode or decode a human face in a real environment. Consequently, our research focuses on the detection of emotions or affective states in a Human-Machine setting. In contrast to other approaches, we use a psychology driven approach trying to minimize complex computations by using a simple dot-based feature extraction method. We suggest a new approach within, but not limited to, a Human-Machine Interface context which detects emotions by analyzing the dynamic change in facial expressions. In order to compare our approach, we discuss our software with respect to other developed facial expression studies in context of its application in a chat environment. Our approach indicates promising results that the program could accurately detect emotions. Implications for further research as well as for applied issues in many areas of Human-Computer Interaction, particularly for affective and social computing, will be discussed and outlined.

KW - Business psychology

KW - Human computer interaction

KW - Human Machine Interface

KW - Affective Computing

KW - Emotional Interfaces

KW - Facial Expression

KW - Human Machine Interface

KW - Engineering

KW - Psychology

KW - Media and communication studies

UR - http://www.scopus.com/inward/record.url?scp=84903219119&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-07230-2_74

DO - 10.1007/978-3-319-07230-2_74

M3 - Article in conference proceedings

SN - 978-3-319-07229-6

VL - 2

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 779

EP - 787

BT - Human-Computer Interaction

A2 - Kurosu, Masaaki

PB - Springer

T2 - 16th International Conference on Human Computer Interaction - HCI 2014

Y2 - 22 June 2014 through 27 June 2014

ER -