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Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems

  • Book
  • © 2021

Overview

Authors:
  1. Luefeng Chen

    1. School of Automation, China University of Geosciences, Wuhan, China

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  2. Min Wu

    1. School of Automation, China University of Geosciences, Wuhan, China

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  3. Witold Pedrycz

    1. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada

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  4. Kaoru Hirota

    1. Tokyo Institute of Technology, Yokohama, Japan

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  • Provides a comprehensive and up-to-date treatise of the area of emotion recognition and understanding by exposing a spectrum of methodological and algorithmic issues
  • Discusses implementations and case studies, identifying the best design practices
  • Assesses business models and practices of the methodology of emotion recognition and understanding as encountered nowadays in emotion robot systems
  • Offers some introductory chapters on the paradigm of emotion recognition and understanding for emotion robot systems so that the book is made self-contained and easily accessible

Part of the book series: Studies in Computational Intelligence (SCI, volume 926)

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Table of contents (14 chapters)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Introduction

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 1-13

  3. Multi-modal Emotion Feature Extraction

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 15-23

  4. Deep Sparse Autoencoder Network for Facial Emotion Recognition

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 25-39

  5. AdaBoost-KNN with Direct Optimization for Dynamic Emotion Recognition

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 41-55

  6. Weight-Adapted Convolution Neural Network for Facial Expression Recognition

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 57-75

  7. Two-Layer Fuzzy Multiple Random Forest for Speech Emotion Recognition

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 77-89

  8. Two-Stage Fuzzy Fusion Based-Convolution Neural Network for Dynamic Emotion Recognition

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 91-114

  9. Multi-support Vector Machine Based Dempster-Shafer Theory for Gesture Intention Understanding

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 115-131

  10. Three-Layer Weighted Fuzzy Support Vector Regressions for Emotional Intention Understanding

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 133-159

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

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 161-182

  12. Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Regression

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 183-214

  13. Emotional Human-Robot Interaction Systems

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 215-222

  14. Experiments and Applications of Emotional Human-Robot Interaction Systems

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages 223-244

  15. Correction to: Dynamic Emotion Understanding Based on Two-Layer Fuzzy Support Vector Regression-Takagi-Sugeno Model

    • Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota
    Pages C1-C1

  16. Back Matter

    Pages 245-247
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Keywords

About this book

This book focuses on the key technologies and scientific problems involved in emotional robot systems, such as multimodal emotion recognition (i.e., facial expression/speech/gesture and their multimodal emotion recognition) and emotion intention understanding, and presents the design and application examples of emotional HRI systems. Aiming at the development needs of emotional robots and emotional human–robot interaction (HRI) systems, this book introduces basic concepts, system architecture, and system functions of affective computing and emotional robot systems. With the professionalism of this book, it serves as a useful reference for engineers in affective computing, and graduate students interested in emotion recognition and intention understanding. This book offers the latest approaches to this active research area. It provides readers with the state-of-the-art methods of multimodal emotion recognition, intention understanding, and application examples of emotional HRI systems.

Authors and Affiliations

  • School of Automation, China University of Geosciences, Wuhan, China

    Luefeng Chen, Min Wu

  • Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada

    Witold Pedrycz

  • Tokyo Institute of Technology, Yokohama, Japan

    Kaoru Hirota

Bibliographic Information

  • Book Title: Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems

  • Authors: Luefeng Chen, Min Wu, Witold Pedrycz, Kaoru Hirota

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-030-61577-2

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

  • Hardcover ISBN: 978-3-030-61576-5Published: 14 November 2020

  • Softcover ISBN: 978-3-030-61579-6Published: 14 November 2021

  • eBook ISBN: 978-3-030-61577-2Published: 13 November 2020

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XI, 247

  • Number of Illustrations: 45 b/w illustrations, 85 illustrations in colour

  • Topics: Computational Intelligence, Robotics and Automation, Robotics

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