Mirroring Emotion System - On-line Synthesizing Facial Expressions on a Robot Face

被引:0
|
作者
Silva, Vinicius [1 ]
Soares, Filomena [2 ]
Esteves, Joao Sena [2 ]
机构
[1] Univ Minho, Sch Engn, Ind Elect Dept, Guimaraes, Portugal
[2] Univ Minho, Sch Engn, Ind Elect Dept, R&D Ctr Algoritmi, Guimaraes, Portugal
来源
2016 8TH INTERNATIONAL CONGRESS ON ULTRA MODERN TELECOMMUNICATIONS AND CONTROL SYSTEMS AND WORKSHOPS (ICUMT) | 2016年
关键词
Facial Expressions; Intel RealSense; Zeno robot; Mimicking Emotions;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Social skills are an important issue throughout human life. Therefore, systems that can synthesize emotions, for example virtual characters (avatars) and robotic platforms, are gaining special attention in the literature. In particular, those systems may be important tools in order to promote social and emotional competences in children (or adults) that have some communication/interaction impairments. The present paper proposes a mirroring emotion system that uses the recent Intel RealSense 3D sensor along with a humanoid robot. The system extracts the user's facial Action Units (AUs) and head motion data. Then, it sends the information to the robot allowing on-line imitation. The first tests were conducted in a laboratorial environment using the software FaceReader in order to verify its correct functioning. Next, a perceptual study was performed to verify the similarity between the expressions of a performer and those of the robot using a quiz distributed to 59 respondents. Finally, the system was evaluated with typically developing children with 6 to 9 years old. The robot mimicked the children's emotional facial expressions. The results point out that the present system can on-line and accurately map facial expressions of a user onto the robot.
引用
收藏
页码:213 / 218
页数:6
相关论文
共 50 条
  • [21] Face robot - Toward realtime-rich facial expressions
    Kobayashi, H
    Ichikawa, Y
    Tsuji, T
    ROBOT AND HUMAN COMMUNICATION, PROCEEDINGS, 2001, : 518 - 523
  • [22] A face attention technique for a robot able to interpret facial expressions
    Simplício C.
    Prado J.
    Dias J.
    IFIP Advances in Information and Communication Technology, 2010, 314 : 335 - 342
  • [23] Experiments on human facial expressions for improvement of simplified robot face
    Takahashi, Yoshihiko
    Hatakeyama, Masanori
    Kanno, Mitsuru
    PROCEEDINGS OF SICE ANNUAL CONFERENCE, VOLS 1-8, 2007, : 477 - 480
  • [24] Dynamic display of facial expressions on the face robot with a life mask
    Hashimoto, Takuya
    Hiramatsu, Sachio
    Tsuji, Toshiaki
    Kobayashi, Hiroshi
    Nihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C, 2009, 75 (749): : 113 - 121
  • [25] A Face Attention Technique for a Robot Able to Interpret Facial Expressions
    Simplicio, Carlos
    Prado, Jose
    Dias, Jorge
    EMERGING TRENDS IN TECHNOLOGICAL INNOVATION, 2010, 314 : 335 - 342
  • [26] Emotion Recognition using Facial Expressions in Children using the NAO Robot
    Lopez-Rincon, Alejandro
    2019 INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND COMPUTERS (CONIELECOMP), 2019, : 146 - 153
  • [27] In the Face of Emotion: A Behavioral Study on Emotions Towards a Robot Using the Facial Action Coding System
    Menne, Isabelle M.
    Lugrin, Birgit
    COMPANION OF THE 2017 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION (HRI'17), 2017, : 205 - 206
  • [28] Dynamic Face Movement Texture Enhances the Perceived Realism of Facial Expressions of Emotion
    Chen, Chaona
    Garrod, Oliver G. B.
    Schyns, Philippe G.
    Jack, Rachael E.
    PROCEEDINGS OF THE 20TH ACM INTERNATIONAL CONFERENCE ON INTELLIGENT VIRTUAL AGENTS (ACM IVA 2020), 2020,
  • [29] Face masks influence emotion judgments of facial expressions: a drift–diffusion model
    W. Craig Williams
    Eisha Haque
    Becky Mai
    Vinod Venkatraman
    Scientific Reports, 13
  • [30] Expression-dependent susceptibility to face distortions in processing of facial expressions of emotion
    Guo, Kun
    Soornack, Yoshi
    Settle, Rebecca
    VISION RESEARCH, 2019, 157 : 112 - 122