Edición de la obra Face Detection and Gesture Recognition for Human-Computer Interaction
| Autor | Ming-Hsuan Yang |
|---|---|
| Editorial | Springer US |
| Fecha de publicación | 2001 |
| Lugar | Boston, MA |
| Idioma | inglés |
| Páginas | 182 |
| Formato | [electronic resource] / |
| ISBN-13 | 9781461355465, 9781461514237 |
| ISBN-10 | 146135546X, 1461514231 |
| OCLC | 852789948 |
| Serie | The International Series in Video Computing -- 1 · International series in video computing -- 1. |
| Número de Cutter | Y22f |
|---|
With the ubiquity of new information technology and media, more effective and friendly methods for human computer interaction (HCI) are being developed which do not rely on traditional devices such as keyboards, mice and displays. The first step for any intelligent HCI system is face detection, and one of most friendly HCI systems is hand gesture. Face Detection and Gesture Recognition for Human-Computer Interaction introduces the frontiers of vision-based interfaces for intelligent human computer interaction with focus on two main issues: face detection and gesture recognition. The first part of the book reviews and discusses existing face detection methods, followed by a discussion on future research. Performance evaluation issues on the face detection methods are also addressed. The second part discusses an interesting hand gesture recognition method based on a generic motion segmentation algorithm. The system has been tested with gestures from American Sign Language with promising results. We conclude this book with comments on future work in face detection and hand gesture recognition. Face Detection and Gesture Recognition for Human-Computer Interaction will interest those working in vision-based interfaces for intelligent human computer interaction. It also contains a comprehensive survey on existing face detection methods, which will serve as the entry point for new researchers embarking on such topics. Furthermore, this book also covers in-depth discussion on motion segmentation algorithms and applications, which will benefit more seasoned graduate students or researchers interested in motion pattern recognition.