Towards Computer Understanding of Human Interactions 1st edition by Iain McCowan, Daniel Gatica Perez, Samy Bengio, Darren Moore, Herve Bourlard ISBN 3540204183 9783540204183

Towards Computer Understanding of Human Interactions 1st edition by Iain McCowan, Daniel Gatica-Perez, Samy Bengio, Darren Moore, Hervé Bourlard – Ebook PDF Instant Download/Delivery. 3540204183, 978-3540204183
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Product details:

ISBN 10:       3540204183
ISBN 13: 978-3540204183
Author:         Iain McCowan, Daniel Gatica-Perez, Samy Bengio, Darren Moore, Hervé Bourlard
 

Towards Computer Understanding of Human Interactions 1st Table of contents:

1. Introduction

   • 1.1 Background and Motivation
   • 1.2 Objectives of the Paper
   • 1.3 Scope of Human Interaction Understanding
   • 1.4 Structure of the Paper

2. Related Work

   • 2.1 Overview of Human-Computer Interaction (HCI) Research
   • 2.2 Approaches to Computer Understanding of Human Behavior
   • 2.3 Advances in Machine Learning for Human Interaction Recognition
   • 2.4 Challenges in Human Interaction Understanding
   • 2.5 Applications of Human Interaction Understanding in Computing

3. Human Interaction Modalities

   • 3.1 Verbal Interactions: Speech and Text Understanding
     • 3.1.1 Speech Recognition Techniques
     • 3.1.2 Natural Language Processing for Text
     • 3.1.3 Dialogue Systems and Conversational Agents
   • 3.2 Non-Verbal Interactions: Gesture and Body Language
     • 3.2.1 Computer Vision for Gesture Recognition
     • 3.2.2 Facial Expression and Emotion Recognition
     • 3.2.3 Posture and Movement Detection
   • 3.3 Contextual and Environmental Awareness
     • 3.3.1 Use of Sensors and IoT in Context Awareness
     • 3.3.2 Environmental Understanding in Human Interaction

4. Technologies for Understanding Human Interaction

   • 4.1 Machine Learning Models for Interaction Recognition
     • 4.1.1 Supervised vs Unsupervised Learning Approaches
     • 4.1.2 Deep Learning and Neural Networks in Interaction Recognition
   • 4.2 Sensor Technologies for Interaction Capture
     • 4.2.1 Wearables and Mobile Sensors
     • 4.2.2 Computer Vision and Camera-based Systems
   • 4.3 Multimodal Interaction Understanding
     • 4.3.1 Integrating Audio, Visual, and Textual Data
     • 4.3.2 Sensor Fusion for Enhanced Interaction Interpretation

5. Human-Centric Computing Systems

   • 5.1 Intelligent Assistants and Virtual Agents
     • 5.1.1 Speech and Gesture-Based Interfaces
     • 5.1.2 Personalized Interaction Systems
   • 5.2 Human-Robot Interaction (HRI)
     • 5.2.1 Interaction Protocols for Collaborative Tasks
     • 5.2.2 Emotion and Intent Recognition in HRI
   • 5.3 Augmented and Virtual Reality Systems
     • 5.3.1 Gesture and Motion Tracking in AR/VR
     • 5.3.2 Virtual Agents in Immersive Environments

6. Challenges in Computer Understanding of Human Interactions

   • 6.1 Ambiguity in Human Behavior and Communication
   • 6.2 Real-Time Processing and Interpretation
   • 6.3 Scalability of Interaction Recognition Systems
   • 6.4 Privacy and Ethical Considerations
   • 6.5 Multicultural and Cross-Cultural Challenges in Interaction Understanding

7. Applications of Human Interaction Understanding

   • 7.1 Healthcare: Patient Monitoring and Assistance
     • 7.1.1 Emotion Recognition for Mental Health Support
     • 7.1.2 Gesture Recognition for Physical Rehabilitation
   • 7.2 Smart Homes and Assistive Technologies
     • 7.2.1 Voice and Gesture-Controlled Home Automation
     • 7.2.2 Context-Aware Assistive Systems for Elderly or Disabled Users
   • 7.3 Autonomous Vehicles: Driver Interaction and Safety
     • 7.3.1 Understanding Driver Attention and Fatigue
     • 7.3.2 Human-Machine Interaction in Self-Driving Cars
   • 7.4 Education and Learning Systems
     • 7.4.1 Adaptive Learning Platforms based on Student Interaction
     • 7.4.2 Human-AI Collaboration in Educational Tools

8. Evaluation of Interaction Understanding Systems

   • 8.1 Metrics for Interaction Recognition Accuracy
   • 8.2 User Experience and Usability Testing
   • 8.3 Case Studies and Experimental Results
   • 8.4 Benchmark Datasets for Human Interaction Recognition

9. Future Directions and Open Challenges

   • 9.1 Advancements in AI for Enhanced Interaction Understanding
   • 9.2 Multimodal Integration for More Natural Interactions
   • 9.3 Cross-Disciplinary Approaches: Neuroscience, Psychology, and Computing
   • 9.4 The Role of Explainability in Interaction Understanding Systems
   • 9.5 Ethical and Societal Implications of Understanding Human Interactions

10. Conclusion

• 10.1 Summary of Key Insights
• 10.2 Potential of Computer Understanding of Human Interactions
• 10.3 Concluding Remarks on the Future of Human-Computer Interaction

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