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.