Emotion Recognition and Understanding for Emotional Human-Robot Interaction Systems

Chapter 1 Introduction

Chapter 2 Multi-modal Emotion Feature Extraction

Chapter 3 Deep Sparse Autoencoder Network for Facial Emotion Recognition

Chapter 4 AdaBoost-KNN with Direct Optimization for Dynamic Emotion Recognition

Chapter 5 Weight-Adapted Convolution Neural Network for Facial Expression Recognition

Chapter 6 Two-Layer Fuzzy Multiple Random Forest for Speech Emotion Recognition

Chapter 7 Two-Stage Fuzzy Fusion Based-Convolution Neural Network for Dynamic Emotion Recognition

Chapter 8 Multi-support Vector Machine Based Dempster-Shafer Theory for Gesture Intention Understanding

Chapter 9 Three-Layer Weighted Fuzzy Support Vector Regressions for Emotional Intention Understanding

Chapter 10 Dynamic Emotion Understanding Based on Two-Layer Fuzzy Support Vector Regression-Takagi-Sugeno Model

Chapter 11 Emotion-Age-Gender-Nationality Based Intention Understanding Using Two-Layer Fuzzy Support Vector Regression

Chapter 12 Emotional Human-Robot Interaction Systems

Chapter 13 Experiments and Applications of Emotional Human-Robot Interaction Systems

Chapter 14 Correction to: Dynamic Emotion Understanding Based on Two-Layer Fuzzy Support Vector Regression-Takagi-Sugeno Model