Gesture Recognition 1st Edition

Grab attention with the definitive resource on human-centered sensing and interpretation: Gesture Recognition — 1st Edition, by Qiguang Miao, Yunan Li, Xiangzeng Liu, and Ruyi Liu. This clear, contemporary guide decodes the theory and practice behind gesture-based interfaces that power modern HCI, robotics, AR/VR, smart homes, and automotive systems.

Explore a balanced, hands-on presentation of core concepts — from signal acquisition and feature extraction to machine learning pipelines, deep-learning architectures, pose estimation, and evaluation metrics. Carefully structured chapters bridge mathematical foundations with practical system design, real-time considerations, and industry-relevant case studies, making complex topics accessible to graduate students, researchers, and engineers alike.

Why this book matters: it translates cutting-edge research into actionable techniques you can apply across sectors worldwide — healthcare monitoring, consumer electronics, manufacturing automation, and intelligent transportation. Readers benefit from clear algorithms, comparative analyses of sensor modalities, and best practices for dataset curation and performance validation.

Whether you’re building prototypes, preparing coursework, or scaling gesture-enabled Books, this edition equips you with the tools to innovate confidently. Concise, authoritative, and forward-looking, it’s an essential reference for anyone working at the intersection of computer vision, signal processing, and human-computer interaction.

Add Gesture Recognition — 1st Edition to your library today and start turning motion into meaningful interaction. Order now to advance your projects and research with a practical, globally relevant guide.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.