Real-Time Vision for Human-Computer Interaction

As computers become prevalent in all aspects of daily life, the need for natural and effective Human-Computer Interaction (HCI) becomes increasingly important. Computer vision and pattern recognition continue to play a dominant role in the HCI realm. However, computer vision methods often fail to become pervasive in the field due to the lack of real-time, robust algorithms, as well as novel and convincing applications.

This state-of-the-art contributed volume presents a series of peer-reviewed survey articles written by international leading experts in computer vision, pattern recognition and Human-Computer Interaction. It is the first published text capturing the latest research in this rapidly advancing field with exclusive focus on real-time algorithms and practical applications in numerous industries, including computer games and medical and automotive systems. It is also an excellent starting point for further research in these areas.

Contributions to this volume address specific topics such as:

Real-Time Algorithms: from Signal Processing to Computer Vision


Recognition of Isolated Fingerspelling Gestures Using Depth Edges


Appearance-Based Real-Time Understanding of Gestures Using Projected Euler Angles


Flocks of Features for Tracking Articulated Objects


Static Hand Posture Recognition Based on Okapi-Chamfer Matching


Visual Modeling of Dynamic Gestures Using 3D Appearance and Motion Features


Head and Facial Animation Tracking Using Appearance-Adaptive Models and Particle Filters


A Real-Time Vision Interface Based on Gaze Detection – Eyekeys


Map Building From Human-Computer Interactions


Real-Time Inference of Complex Mental States from Facial Expressions and Head Gestures


Epipolar Constrained User Pushbutton Selection in Projected Interfaces


Vision-Based HCI Applications


The Office of the Past


MPEG-4 Face and Body Animation Coding Applied to HCI


Multimodal Human-Computer Interaction


Real-Time Vision for Human-Computer Interaction is an invaluable reference for HCI researchers in both academia and industry, and a useful supplement for advanced-level courses in HCI and Computer Vision.