Dynamic Emotion Understanding Based on Two-Layer Fuzzy Fuzzy Support Vector Regression-Takagi-Sugeno Model

Luefeng Chen; Min Wu; Witold Pedrycz; Kaoru Hirota

doi:10.1007/978-3-030-61577-2_10

Dynamic Emotion Understanding Based on Two-Layer Fuzzy Fuzzy Support Vector Regression-Takagi-Sugeno Model

Luefeng Chen^*, Min Wu, Witold Pedrycz, Kaoru Hirota

^*此作品的通讯作者

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

摘要

Two-layer Fuzzy SVR-TS Model is proposed for emotion understanding in human-robot interaction, where the real-time dynamic emotion is recognized according to facial expression, and emotional intention understanding is obtained mainly based on human emotions and identification information. It aims to make robots capable of recognizing and understanding human emotions, in such a way that make humanrobot interaction run smoothly.

源语言	英语
主期刊名	Studies in Computational Intelligence
出版商	Springer Science and Business Media Deutschland GmbH
页	161-182
页数	22
DOI	https://doi.org/10.1007/978-3-030-61577-2_10
出版状态	已出版 - 2021
已对外发布	是

出版系列

姓名	Studies in Computational Intelligence
卷	926
ISSN（印刷版）	1860-949X
ISSN（电子版）	1860-9503

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10.1007/978-3-030-61577-2_10

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Chen, L., Wu, M., Pedrycz, W., & Hirota, K. (2021). Dynamic Emotion Understanding Based on Two-Layer Fuzzy Fuzzy Support Vector Regression-Takagi-Sugeno Model. 在 Studies in Computational Intelligence (页码 161-182). (Studies in Computational Intelligence; 卷 926). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-61577-2_10

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abstract = "Two-layer Fuzzy SVR-TS Model is proposed for emotion understanding in human-robot interaction, where the real-time dynamic emotion is recognized according to facial expression, and emotional intention understanding is obtained mainly based on human emotions and identification information. It aims to make robots capable of recognizing and understanding human emotions, in such a way that make humanrobot interaction run smoothly.",

author = "Luefeng Chen and Min Wu and Witold Pedrycz and Kaoru Hirota",

note = "Publisher Copyright: {\textcopyright} 2020, The Author(s), under exclusive license to Springer Nature Switzerland AG.",

year = "2021",

doi = "10.1007/978-3-030-61577-2_10",

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Dynamic Emotion Understanding Based on Two-Layer Fuzzy Fuzzy Support Vector Regression-Takagi-Sugeno Model. / Chen, Luefeng; Wu, Min; Pedrycz, Witold 等.
Studies in Computational Intelligence. Springer Science and Business Media Deutschland GmbH, 2021. 页码 161-182 (Studies in Computational Intelligence; 卷 926).

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

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T1 - Dynamic Emotion Understanding Based on Two-Layer Fuzzy Fuzzy Support Vector Regression-Takagi-Sugeno Model

AU - Chen, Luefeng

AU - Wu, Min

AU - Pedrycz, Witold

AU - Hirota, Kaoru

PY - 2021

Y1 - 2021

N2 - Two-layer Fuzzy SVR-TS Model is proposed for emotion understanding in human-robot interaction, where the real-time dynamic emotion is recognized according to facial expression, and emotional intention understanding is obtained mainly based on human emotions and identification information. It aims to make robots capable of recognizing and understanding human emotions, in such a way that make humanrobot interaction run smoothly.

AB - Two-layer Fuzzy SVR-TS Model is proposed for emotion understanding in human-robot interaction, where the real-time dynamic emotion is recognized according to facial expression, and emotional intention understanding is obtained mainly based on human emotions and identification information. It aims to make robots capable of recognizing and understanding human emotions, in such a way that make humanrobot interaction run smoothly.

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T3 - Studies in Computational Intelligence

SP - 161

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BT - Studies in Computational Intelligence

PB - Springer Science and Business Media Deutschland GmbH

ER -

Dynamic Emotion Understanding Based on Two-Layer Fuzzy Fuzzy Support Vector Regression-Takagi-Sugeno Model

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