Real-Time Vision for Human-Computer Interaction

This state-of-the-art contributed volume presents a series of peer-reviewed survey articles by top 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. Contributors discuss topics such as Vision-Based Fingerspelling and Hand Gesture Recognition, Head and Facial Animation Tracking, Real-Time Vision Interfaces, and Map Building from Human-Computer Interactions. It is an invaluable reference for researchers and practitioners in the areas of Human-Computer Interaction and computer vision, and an excellent starting point for further research because it outlines further challenges in these fields.

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.