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Gesture Recognition

Theory and Applications

  • 1st Edition - July 9, 2024
  • Latest edition
  • Authors: Qiguang Miao, Yunan Li, Xiangzeng Liu, Ruyi Liu
  • Language: English

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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Description

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.

Key features

  • 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

Readership

All researchers engaged in computer vision and artificial intelligence

Table of contents

1. Basic Concepts and Development of Gesture Recognition

2. Common Datasets in Gesture Recognition

3. Handcrafted Features Based Gesture Recognition Methods

4. Convolutional Neural Networks Based Gesture Recognition Methods

5. Gesture Recognition Methods Based on Recurrent Neural Networks and Variants

6. Multimodal Data Fusion Based Gesture Recognition Methods

7. Gesture Recognition and Attention Mechanism

8. Human-Computer Interaction Cases Based on Gesture Recognition

9. Development Discussion on the Application of Gesture Recognition in Future HumanComputer Interaction

Product details

  • Edition: 1
  • Latest edition
  • Published: July 9, 2024
  • Language: English

About the authors

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, China

YL

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, China

XL

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, China

RL

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, China

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