In this paper, we introduce a 3-D human-body tracker capable of handling fast and complex motions in real-time. The parameter space, augmented with first order derivatives, is automatically partitioned into Gaussian clusters each representing an elementary motion: hypothesis propagation inside each cluster is therefore accurate and efficient. The transitions between clusters use the predictions of a Variable Length Markov Model which can explain highlevel behaviours over a long history. Using Monte-Carlo methods, evaluation of model candidates is critical for both speed and robustness. We present a new evaluation scheme based on volumetric reconstruction and blobs-fitting, where appearance models and image evidences are represented by Gaussian mixtures. We demonstrate the application of our tracker to long video sequences exhibiting rapid and diverse movements. 1

We present an approach for enriching a virtual environment by augmenting it with the kind of naturalistic clutter often found in real-world scenes. Rather than manually specifying clutter distribution, our semi-automatic procedural approach seeks to add plausible clutter with minimal user-interaction, and few constraints on the format in which the virtual environment is specified. We suggest that the integration of suitable and plausible clutter to a virtual environment increases realism at low cost

This paper presents a robust method for real-time visual human body tracking. We perform a hierarchical 3D reconstruction from multiple camera views as a basis for tracking. Blobs attached to a kinematic model are then used to reliably track individual body parts with both volume and color information. We describe how the blob-model is dynamically adjusted to accommodate different body configurations. In tests, our system has proved robust in presence of noisy data and self-occlusions.

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.

The problem of recovering the shape of objects from three-dimensional data is important to many areas of computer graphics and vision. We present here a method for the recovery of single-part objects from unstructured 3D points sets, based on the fitting of deformable superquadric models. The limitations of least-squares minimisation as a technique for fitting superquadric models are discussed. After investigating the possibility of using a genetic algorithm as an alternative, we propose a hybrid approach to the recovery of deformable superquadrics based on a two-stage fitting process that combines a genetic algorithm and nonlinear least-squares minimization.

Physically-based modelling is a powerful technique for specifying the laws and characteristics of virtual environments (VEs) and the objects they contain. In this paper, we describe Iota, a component framework for creating and interacting with multi-body physically-based models in VEs. In conclusion, we present two case studies implemented within the framework.

Photometric reconstruction is the process of estimating the illumination and surface reflectance properties of an environment, given a geometric model of the scene and a set of photographs of its surfaces. For mixed-reality applications, such data is required if synthetic objects are to be correctly illuminated or if synthetic light sources are to be used to re-light the scene. Current methods of estimating such data are limited in the practical situations in which they can be applied, due to the fact that the geometric and radiometric models of the scene which are provided by the user must be complete, and that the position (and in some cases, intensity) of the light sources must also be specified a-priori. In this paper, a novel algorithm is presented which overcomes these constraints, and allows photometric data to be reconstructed in less restricted situations. This is achieved through the use of virtual light sources which mimic the effect of direct illumination from unknown luminaires, and indirect illumination reflected off unknown geometry. The intensity of these virtual light sources and the surface material properties are estimated using an iterative algorithm which attempts to match calculated radiance values to those observed in photographs. Results are presented for both synthetic and real scenes that show the quality of the reconstructed data and its use in off-line mixed-reality applications.

There are many real-world applications of Virtual Reality that require the construction of complex and accurate three-dimensional models, suitably structured for interactive manipulation. In this paper, we present semi-automatic methods that allow such environments to be quickly and easily built from photographs taken with uncalibrated cameras, and illustrate the techniques by application to the real-world problem of scene-of-crime reconstruction.

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.

The Programmer’s Hierarchical Interactive Graphics System (PHIGS) is an International Standard for integrating application modelling and interactive computer graphics. With PHIGS, application models are constructed from hierarchical data structures called structure networks, which may be edited interactively. While structure networks are in principle straightforward to create, organising and managing them correctly is in practice a much more difficult proposition. One of the main difficulties arises from the atomic nature of the traversal process by which structure networks are interpreted for display. This paper draws an analogy between structure network traversal and programming language execution, and presents the PHIGS Debugger, a development tool for PHIGS applications. The PHIGS Debugger supports interactive incremental traversal of structure networks and debugging of the PHIGS Centralised Structure Store, and is a component of the PHIGS Toolkit, an emerging set of portable integrated tools for PHIGS environments. 1

Abstract The Programmer's Hierarchical Interactive Graphics System (PHIGS) is an International Standard for computer graphics. PHIGS provides a flexible mechanism for creating hierarchical models from collections of directed acyclic graphs known as ‘structure networks’. In practice, the combination of powerful data structuring facilities and the ability to dynamically edit structure networks can lead to a potential complexity which makes models difficult to manage and maintain reliably. This paper presents TopDraw, a portable programming tool for visualising PHIGS structure networks, by automatically documenting their topology using diagrams. Drawing tidy representations of graphs algorithmically is a difficult problem, and most existing systems are large, complex and speciallsed The alternative approach taken in TopDraw is to use a fast, straightforward algorithm supplemented when necessary by an interactive 'tidief. A novel feature of TopDraw is that the diagrams it produces are themselves PHIGS structures, which the application may edit and manipdate as required. TopDraw is a component of the PHIGS Toolkit, an emerging set of portable integrated tools for PHIGS environments.

The Programmer’s Hierarchical Interactive Graphics System (PHIGS), currently under development by ISO, is a specification of a set of functions for device-independent computer graphics programming, supporting dynamic interaction and hierarchically organised graphical data. A central aspect of an implementation of a system such as PHIGS is the provision of a compact and efficient representation for the graphical entities involved. This paper describes a centralised graphical database for KRT³, an experimental hierarchical graphics system based on PHIGS. It presents a discussion of the issues involved, and the experience gained, in the practical design and implementation of a database for hierarchical graphical data. A novel aspect of the design is that the database may be simultaneously shared by several application programs.