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Introduction

In recent years, the field of human-robot interaction (HRI) has seen significant advancements, with robots being used in various applications such as healthcare, education, and entertainment. Emotion recognition plays a crucial role in HRI, as it enables robots to understand and respond to human emotions effectively. Computer vision techniques have been widely used for emotion recognition in HRI, as they allow robots to analyze facial expressions and body language to infer human emotions.

This thesis explores the use of computer vision for emotion recognition in human-robot interaction. The goal is to develop a system that can accurately recognize and respond to human emotions in real-time, thus enhancing the overall user experience in HRI applications. By understanding human emotions, robots can tailor their interactions to better meet the needs and preferences of users, leading to more effective communication and collaboration between humans and robots.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review
2.1 Overview of human-robot interaction
2.2 Emotion recognition in HRI
2.3 Computer vision techniques for emotion recognition
2.4 Existing systems for emotion recognition in HRI
2.5 Challenges in emotion recognition using computer vision
2.6 Advances in machine learning algorithms for emotion recognition
2.7 Ethical considerations in HRI
2.8 User experience in HRI
2.9 Social impact of emotion recognition in HRI
2.10 Future trends in emotion recognition in HRI

Chapter 3: System Design and Methodology
3.1 System architecture
3.2 Data collection and preprocessing
3.3 Feature extraction techniques
3.4 Emotion classification algorithms
3.5 Real-time emotion recognition system
3.6 Integration with robot platforms
3.7 Performance evaluation metrics
3.8 User studies and feedback

Chapter 4: System Implementation
4.1 Software and hardware requirements
4.2 Implementation of computer vision algorithms
4.3 Integration with HRI platforms
4.4 Testing and validation
4.5 Performance optimization techniques
4.6 System deployment and maintenance
4.7 User training and support

Chapter 5: Conclusion and Summary
5.1 Summary of key findings
5.2 Contributions to the field
5.3 Future research directions
5.4 Implications for HRI applications
5.5 Conclusion

Thesis Overview

The thesis on “Computer vision for emotion recognition in human-robot interaction” aims to explore the use of computer vision techniques for enhancing emotion recognition in interactions between humans and robots. The introduction provides an overview of the research topic, highlighting the importance of emotion recognition in HRI and the role of computer vision in achieving this goal.

The literature review examines existing studies and systems in the field of human-robot interaction, emotion recognition, and computer vision. It discusses challenges, advances, and trends in the field, as well as ethical considerations and user experience in HRI. The chapter lays the foundation for the system design and methodology, where the architecture, data collection, feature extraction, and classification algorithms for emotion recognition are detailed.

The system implementation chapter focuses on the practical aspects of building the real-time emotion recognition system, including software and hardware requirements, integration with robot platforms, testing, and validation. The conclusion and summary chapter wraps up the thesis by summarizing key findings, contributions, future research directions, and implications for HRI applications.

Overall, this thesis aims to advance the field of human-robot interaction by developing a system that can accurately recognize and respond to human emotions using computer vision techniques. It is hoped that the research will contribute to improving user experience, communication, and collaboration between humans and robots in various applications.

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