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.

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

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Yes, you can access Gesture Recognition by Qiguang Miao,Yunan Li,Xiangzeng Liu,Ruyi Liu in PDF and/or ePUB format, as well as other popular books in Design & UI/UX Design. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Elsevier

Year

2024

ISBN

9780443289606

Topic

Design

Subtopic

UI/UX Design

Cover image
Title page
Table of Contents
Copyright
Chapter 1. Basic concepts and development of gesture recognition
Chapter 2. Common datasets in the field of gesture recognition
Chapter 3. Gesture recognition method based on handicraft features
Chapter 4. Gesture recognition method based on convolutional neural network
Chapter 5. Enhancing gesture recognition with advanced recurrent neural networks and memory networks
Chapter 6. Gesture recognition method based on multimodal data fusion
Chapter 7. Gesture recognition and attention mechanisms
Chapter 8. Gesture recognition-based human–computer interaction cases
Chapter 9. Exploring development of gesture recognition for future human–computer interaction applications
Index