Rawal, Niyati ; Stock-Homburg, Ruth (2022)
Facial Emotion Expressions in Human–Robot Interaction: A Survey.
In: International Journal of Social Robotics
doi: 10.1007/s12369-022-00867-0
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Facial expressions are an ideal means of communicating one’s emotions or intentions to others. This overview will focus on human facial expression recognition as well as robotic facial expression generation. In the case of human facial expression recognition, both facial expression recognition on predefined datasets as well as in real-time will be covered. For robotic facial expression generation, hand-coded and automated methods i.e., facial expressions of a robot are generated by moving the features (eyes, mouth) of the robot by hand-coding or automatically using machine learning techniques, will also be covered. There are already plenty of studies that achieve high accuracy for emotion expression recognition on predefined datasets, but the accuracy for facial expression recognition in real-time is comparatively lower. In the case of expression generation in robots, while most of the robots are capable of making basic facial expressions, there are not many studies that enable robots to do so automatically. In this overview, state-of-the-art research in facial emotion expressions during human–robot interaction has been discussed leading to several possible directions for future research.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2022 |
| Autor(en): | Rawal, Niyati ; Stock-Homburg, Ruth |
| Art des Eintrags: | Bibliographie |
| Titel: | Facial Emotion Expressions in Human–Robot Interaction: A Survey |
| Sprache: | Englisch |
| Publikationsjahr: | 24 Juni 2022 |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | International Journal of Social Robotics |
| DOI: | 10.1007/s12369-022-00867-0 |
| Kurzbeschreibung (Abstract): | Facial expressions are an ideal means of communicating one’s emotions or intentions to others. This overview will focus on human facial expression recognition as well as robotic facial expression generation. In the case of human facial expression recognition, both facial expression recognition on predefined datasets as well as in real-time will be covered. For robotic facial expression generation, hand-coded and automated methods i.e., facial expressions of a robot are generated by moving the features (eyes, mouth) of the robot by hand-coding or automatically using machine learning techniques, will also be covered. There are already plenty of studies that achieve high accuracy for emotion expression recognition on predefined datasets, but the accuracy for facial expression recognition in real-time is comparatively lower. In the case of expression generation in robots, while most of the robots are capable of making basic facial expressions, there are not many studies that enable robots to do so automatically. In this overview, state-of-the-art research in facial emotion expressions during human–robot interaction has been discussed leading to several possible directions for future research. |
| Fachbereich(e)/-gebiet(e): | 01 Fachbereich Rechts- und Wirtschaftswissenschaften 01 Fachbereich Rechts- und Wirtschaftswissenschaften > Betriebswirtschaftliche Fachgebiete 01 Fachbereich Rechts- und Wirtschaftswissenschaften > Betriebswirtschaftliche Fachgebiete > Fachgebiet Marketing & Personalmanagement |
| Hinterlegungsdatum: | 30 Jun 2022 09:23 |
| Letzte Änderung: | 18 Sep 2022 11:38 |
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