No abstract available.

Camera tracking is a fundamental requirement for video-based augmented reality applications. The ability to accurately calculate the intrinsic and extrinsic camera parameters for each frame of a video sequence is essential if synthetic objects are to be integrated into the image data in a believable way. In this paper, we present an accurate and reliable approach to camera calibration for off-line video-based augmented reality applications. We first describe an improved feature tracking algorithm, based on the widely used Kanade-Lucas-Tomasi tracker. Estimates of inter-frame camera motion are used to guide tracking, greatly reducing the number of incorrectly tracked features. We then present a robust hierarchical scheme that merges sub-sequences together to form a complete projective reconstruction. Finally, we describe how RANSAC-based random sampling can be applied to the problem of self-calibration, allowing for more reliable upgrades to metric geometry. Results of applying our calibration algorithms are given for both synthetic and real data.

Virtual environments present opportunities for novel interaction with and visualisation of abstract data. However, the inherent difficulties of rendering 3D environments, as well as bottlenecks in traditional virtual reality systems, make real-time manipulation of realistic amounts of data difficult. We present QSPACE, a data visualisation tool with which we have begun to explore techniques and architectures for making real-time interaction with largest amounts of data possible.

In this paper we present work undertaken by the Advanced Interfaces Group at the University of Manchester on the design and development of a system to support large numbers of geographically distributed users in complex, large-scale virtual environments (VEs).We shown how the problem of synchronisation in the face of network limitations is being addressed by the Deva system through the exploitation of subjectivity. Further, we present a model for flexibly describing object behaviours in the VEs.Applications of the system in use are described.

This paper describes a publicly available virtual reality (VR) system, GNU/MAVERIK, which forms one component of a complete 'VR operating system'. We give an overview of the architecture of MAVERIK, and show how it is designed to use application data in an intelligent way, via a simple, yet powerful, callback mechanism which supports an object-oriented framework of classes, objects and methods. Examples are given which illustrate different uses of the system, and typical performance levels.