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