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Gesture Recognition
Theory and Applications
- 1st Edition - July 9, 2024
- Authors: Qiguang Miao, Yunan Li, Xiangzeng Liu, Ruyi Liu
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 8 9 5 9 - 0
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 8 9 6 0 - 6
Gesture Recognition: Theory and Applications covers this important topic in computer science and language technology that has a goal of interpreting human gestures via mathem… Read more
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Request a sales quoteGesture 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.
Three gesture recognition-based HCI (Human Computer Interaction) practical cases are introduced. Finally, the book looks at emerging research trends and application.
- Focuses on the theory and application of gesture recognition, providing a systematic introduction to commonly used datasets in the field as well as algorithms based on handcrafted features, convolutional neural networks, multimodal fusion, and attention mechanisms
- Introduces the practical applications of gesture recognition in real-world scenarios, enabling readers to enhance their practical application skills while learning about relevant technologies
- Demonstrates four main categories of gesture recognition methods and analyzes their associated challenges
All researchers engaged in computer vision and artificial intelligence
- Cover image
- Title page
- Table of Contents
- Copyright
- Chapter 1. Basic concepts and development of gesture recognition
- Abstract
- 1.1 Principles of gesture recognition
- 1.2 Development of gesture recognition algorithms
- 1.3 Current challenges in the field of gesture recognition
- 1.4 Summary
- References
- Chapter 2. Common datasets in the field of gesture recognition
- Abstract
- 2.1 Image-based gesture dataset
- 2.2 Video-based gesture dataset
- 2.3 Dataset summary
- 2.4 Summary
- References
- Chapter 3. Gesture recognition method based on handicraft features
- Abstract
- 3.1 Hand region segmentation
- 3.2 Gesture feature extraction
- 3.3 Gesture recognition
- 3.4 Summary
- References
- Chapter 4. Gesture recognition method based on convolutional neural network
- Abstract
- 4.1 Basic operations of deep convolutional neural network
- 4.2 Application of 2D convolutional neural network in gesture recognition
- 4.3 Basic operations of 3D convolutional neural network
- 4.4 Application of 3D convolutional neural network in gesture recognition
- 4.5 Summary
- References
- Chapter 5. Enhancing gesture recognition with advanced recurrent neural networks and memory networks
- Abstract
- 5.1 Overview of development of recurrent neural networks
- 5.2 Recurrent neural networks and their variants
- 5.3 Memory network combined with external storage units
- 5.4 Application of recurrent neural network in gesture recognition
- 5.5 Summary
- References
- Chapter 6. Gesture recognition method based on multimodal data fusion
- Abstract
- 6.1 Techniques for acquiring multimodal data
- 6.2 Fusion algorithm of different modality data
- 6.3 Summary
- References
- Chapter 7. Gesture recognition and attention mechanisms
- Abstract
- 7.1 Concept of attention mechanism
- 7.2 Attention mechanism as preprocess for gesture recognition
- 7.3 Attention mechanism based on complementarity of different modal data
- 7.4 Summary
- References
- Chapter 8. Gesture recognition-based human–computer interaction cases
- Abstract
- 8.1 Application areas of gesture recognition
- 8.2 Gesture recognition case studies
- 8.3 Summary
- References
- Chapter 9. Exploring development of gesture recognition for future human–computer interaction applications
- Abstract
- 9.1 New gesture recognition technology for human–computer interaction
- 9.2 New applications of gesture recognition in human–computer interaction
- 9.3 Summary
- References
- Index
- No. of pages: 224
- Language: English
- Edition: 1
- Published: July 9, 2024
- Imprint: Elsevier
- Paperback ISBN: 9780443289590
- eBook ISBN: 9780443289606
QM
Qiguang Miao
Professor Qiguang Miao is based at the School of Computer Science and Technology, Xidian University, China. He received his PhD degree from Xidian University in 2005. He is now the dean of school of networking and continuing education in Xidian University. His research interests include intelligent image/video understanding and big data.
Affiliations and expertise
Xidian University, ChinaYL
Yunan Li
Yunan Li is an associate professor based at the School of Computer Science and Technology, Xidian University, China. His research interests include computer vision, image/video enhancement and intelligent human behavior analysis.
Affiliations and expertise
Xidian University, ChinaXL
Xiangzeng Liu
Xiangzeng Liu is an associate professor based at the School of Computer Science and Technology, Xidian University, China. His research interests include multi-source remote sensing image registration and fusion, target recognition and tracking, infrared image nonuniformity correction.
Affiliations and expertise
Xidian University, ChinaRL
Ruyi Liu
Dr Ruyi Liu is based at the School of Computer Science and Technology, Xidian University, China. Dr Liu received her PhD degree from Xidian University in 2018. Dr Liu has published over 20 papers on international journals or conferences.
Affiliations and expertise
Xidian University, ChinaRead Gesture Recognition on ScienceDirect