Computer Vision in Human-Computer Interaction ECCV 2004 Workshop on HCI, Prague, Czech Republic, May 16, 2004, Proceedings

This book constitutes the refereed proceedings of the International Workshop on Human-Computer Interaction, HCI 2004, held at ECCV 2004 in Prague, Czech Republic in May 2004.

The 19 revised full papers presented together with an introductory overview and an invited paper were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on human-robot interaction, gesture recognition and body tracking, systems, and face and head.

The State-of-the-Art in Human-Computer Interaction.- The State-of-the-Art in Human-Computer Interaction.- Invited Presentation.- Practical Interface Experiments with Implant Technology.- Human-Robot Interaction.- Motivational System for Human-Robot Interaction.- Real-Time Person Tracking and Pointing Gesture Recognition for Human-Robot Interaction.- A Vision-Based Gestural Guidance Interface for Mobile Robotic Platforms.- Gesture Recognition and Body Tracking.- Virtual Touch Screen for Mixed Reality.- Typical Sequences Extraction and Recognition.- Arm-Pointer: 3D Pointing Interface for Real-World Interaction.- Hand Gesture Recognition in Camera-Projector System*.- Authentic Emotion Detection in Real-Time Video.- Hand Pose Estimation Using Hierarchical Detection.- Systems.- Exploring Interactions Specific to Mixed Reality 3D Modeling Systems.- 3D Digitization of a Hand-Held Object with a Wearable Vision Sensor.- Location-Based Information Support System Using Multiple Cameras and LED Light Sources with the Compact Battery-Less Information Terminal (CoBIT).- Djinn: Interaction Framework for Home Environment Using Speech and Vision.- A Novel Wearable System for Capturing User View Images.- An AR Human Computer Interface for Object Localization in a Cognitive Vision Framework.- Face and Head.- EM Enhancement of 3D Head Pose Estimated by Perspective Invariance.- Multi-View Face Image Synthesis Using Factorization Model.- Pose Invariant Face Recognition Using Linear Pose Transformation in Feature Space.- Model-Based Head and Facial Motion Tracking.