Chen, C. , Garrod, O. G.B., Zhan, J., Beskow, J., Schyns, P. G. and Jack, R. E. (2018) Reverse Engineering Psychologically Valid Facial Expressions of Emotion into Social Robots. In: 13th IEEE International Conference on Automatic Face and Gesture Recognition, Xi'an, China, 15-19 May 2018, pp. 448-452. ISBN 9781538623350 (doi: 10.1109/FG.2018.00072)
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Abstract
Social robots are now part of human society, destined for schools, hospitals, and homes to perform a variety of tasks. To engage their human users, social robots must be equipped with the essential social skill of facial expression communication. Yet, even state-of-the-art social robots are limited in this ability because they often rely on a restricted set of facial expressions derived from theory with well-known limitations such as lacking naturalistic dynamics. With no agreed methodology to objectively engineer a broader variance of more psychologically impactful facial expressions into the social robots' repertoire, human-robot interactions remain restricted. Here, we address this generic challenge with new methodologies that can reverse-engineer dynamic facial expressions into a social robot head. Our data-driven, user-centered approach, which combines human perception with psychophysical methods, produced highly recognizable and human-like dynamic facial expressions of the six classic emotions that generally outperformed state-of-art social robot facial expressions. Our data demonstrates the feasibility of our method applied to social robotics and highlights the benefits of using a data-driven approach that puts human users as central to deriving facial expressions for social robots. We also discuss future work to reverse-engineer a wider range of socially relevant facial expressions including conversational messages (e.g., interest, confusion) and personality traits (e.g., trustworthiness, attractiveness). Together, our results highlight the key role that psychology must continue to play in the design of social robots.
Item Type: | Conference Proceedings |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Jack, Professor Rachael and Garrod, Dr Oliver and Schyns, Professor Philippe and Chen, Dr Chaona and Zhan, Dr Jiayu |
Authors: | Chen, C., Garrod, O. G.B., Zhan, J., Beskow, J., Schyns, P. G., and Jack, R. E. |
College/School: | College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience College of Science and Engineering > School of Psychology |
ISBN: | 9781538623350 |
Copyright Holders: | Copyright © 2018 The Authors |
Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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