Gesture Recognition: Theory and Applications covers this important topic in computer science and language technology that has a goal of interpreting human gestures via mathematical algorithms. The book begins by examining the computer vision-based gesture recognition method, focusing on the theory and related research results of various recent gesture recognition technologies. The book takes the evolutions of gesture recognition technology as a clue, systematically introducing gesture recognition methods based on handcrafted features, convolutional neural networks, recurrent neural networks, multimodal data fusion, and visual attention mechanisms.
Three gesture recognition-based HCI (Human Computer Interaction) practical cases are introduced. Finally, the book looks at emerging research trends and application.
1. Gesture Recognition - p. Page i 2. Cover - p. Page i 3. Title page - p. Page ii 4. Table of Contents - p. Page iii 5. Copyright - p. Page iii 6. Contents - p. Page vi 7. List of Illustrations - p. Page vii 8. List of Tables - p. Page viii 9. Chapter 1 : Basic concepts and development of gesture recognition - p. Page viii 10. Chapter 2 : Common datasets in the field of gesture recognition - p. Page 12 11. Chapter 3 : Gesture recognition method based on handicraft features - p. Page 32 12. Chapter 4 : Gesture recognition method based on convolutional neural network - p. Page 73 13. Chapter 5 : Enhancing gesture recognition with advanced recurrent neural networks and memory networks - p. Page 98 14. Chapter 6 : Gesture recognition method based on multimodal data fusion - p. Page 119 15. Chapter 7 : Gesture recognition and attention mechanisms - p. Page 150 16. Chapter 8 : Gesture recognition-based human–computer interaction cases - p. Page 170 17. Chapter 9 : Exploring development of gesture recognition for future human–computer interaction applications - p. Page 193 18. Index - p. Page 204
Gesture Recognition: Theory and Applications covers this important topic in computer science and language technology that has a goal of interpreting human gestures via mathematical algorithms. The book begins by examining the computer vision-based gesture recognition method, focusing on the theory and related research results of various recent gesture recognition technologies. The book takes the evolutions of gesture recognition technology as a clue, systematically introducing gesture recognition methods based on handcrafted features, convolutional neural networks, recurrent neural networks, multimodal data fusion, and visual attention mechanisms.
Three gesture recognition-based HCI (Human Computer Interaction) practical cases are introduced. Finally, the book looks at emerging research trends and application.
1. Gesture Recognition - p. Page i 2. Cover - p. Page i 3. Title page - p. Page ii 4. Table of Contents - p. Page iii 5. Copyright - p. Page iii 6. Contents - p. Page vi 7. List of Illustrations - p. Page vii 8. List of Tables - p. Page viii 9. Chapter 1 : Basic concepts and development of gesture recognition - p. Page viii 10. Chapter 2 : Common datasets in the field of gesture recognition - p. Page 12 11. Chapter 3 : Gesture recognition method based on handicraft features - p. Page 32 12. Chapter 4 : Gesture recognition method based on convolutional neural network - p. Page 73 13. Chapter 5 : Enhancing gesture recognition with advanced recurrent neural networks and memory networks - p. Page 98 14. Chapter 6 : Gesture recognition method based on multimodal data fusion - p. Page 119 15. Chapter 7 : Gesture recognition and attention mechanisms - p. Page 150 16. Chapter 8 : Gesture recognition-based human–computer interaction cases - p. Page 170 17. Chapter 9 : Exploring development of gesture recognition for future human–computer interaction applications - p. Page 193 18. Index - p. Page 204
