Hao Kong – författare

This book introduces human reconstruction technologies in smart homes leveraging mmWave signals. It begins by presenting the overview of human reconstruction and the development of mmWave sensing technology. The authors introduce a mmWave sensing-based human posture reconstruction approach, which exploits mmWave signals to sense and track multiple users’ postures as they move, walk or sit. It also presents a facial expression reconstruction system that reconstructs 3D human faces and continuously exhibits facial expressions using mmWave.  The authors describe a hand gesture reconstruction system that utilizes mmWave signals to generate 3D hand skeletons and reconstruct hand meshes. A thorough investigation of state-of-art research work is further presented covering human reconstruction, mmWave sensing and mmWave-based human reconstruction. Finally, conclusions and the direction of future research are highlighted for this book.Human and the cyberworld are moving towards high synchronization as more IoT devices are integrated in smart homes. By reconstructing human postures, facial expressions, and hand gestures in the cyberworld, a virtual human avatar can map the state of human into the physical world and deeply integrate reality and virtuality. The process strongly energizes emerging applications such as virtual reality, augmented reality, meta-universe, immersive games, etc. This book targets graduate-level students majoring in the computer science and engineering, and electrical engineering. Professionals working in wireless signal-based human sensing will also find this book a valuable resource.

This book introduces human reconstruction technologies in smart homes leveraging mmWave signals. It begins by presenting the overview of human reconstruction and the development of mmWave sensing technology. The authors introduce a mmWave sensing-based human posture reconstruction approach, which exploits mmWave signals to sense and track multiple users’ postures as they move, walk or sit. It also presents a facial expression reconstruction system that reconstructs 3D human faces and continuously exhibits facial expressions using mmWave.  The authors describe a hand gesture reconstruction system that utilizes mmWave signals to generate 3D hand skeletons and reconstruct hand meshes. A thorough investigation of state-of-art research work is further presented covering human reconstruction, mmWave sensing and mmWave-based human reconstruction. Finally, conclusions and the direction of future research are highlighted for this book. Human and the cyberworld are moving towards high synchronization as more IoT devices are integrated in smart homes. By reconstructing human postures, facial expressions, and hand gestures in the cyberworld, a virtual human avatar can map the state of human into the physical world and deeply integrate reality and virtuality. The process strongly energizes emerging applications such as virtual reality, augmented reality, meta-universe, immersive games, etc.  This book targets graduate-level students majoring in the computer science and engineering, and electrical engineering. Professionals working in wireless signal-based human sensing will also find this book a valuable resource.

As a privacy-preserving and illumination-robust manner, WiFi signal-based user authentication has become a new direction for ubiquitous user authentication to protect user privacy and security. It gradually turns into an important option for addressing the security concern of IoT environment.However, due to the limited sensing capability of WiFi signals and wide application scenarios, WiFi signal-based user authentication suffers from practical issues of diversified behaviors and complex scenarios.Therefore, it is necessary to address the issues and build integrated systems for user authentication using WiFi signals. In this book, the development and progress of WiFi signal-based user authentication systems in extensive scenarios are presented, which provides a new direction and solution for ubiquitous security and privacy protection. This book gives strong motivation of leveraging WiFi signals to sense human activities for user authentication, and presents the keyissues of WiFi-based user authentication in diversified behaviors and complex scenarios. This book provides the approaches for digging WiFi signals to sense human activities and extract features, realizing user authentication under fine-grained finger gestures, undefined body gestures, and multi-user scenarios. State-of-the-art researches and future directions involved with WiFi signal-based user authentication are presented and discussed as well. This book will benefit researchers and practitioners in the related field.