Many virtual reality (VR) applications use teleport for locomotion. The non-continuous locomotion of is suited VR controllers and can minimize simulator sickness, but it also reduce spatial awareness compared to continuous Our aim was create continuous, controller-based techniques that would support awareness. We the new techniques, slider grab, with in a task where participants counted small v...

An important issue in tracking is how to incorporate an appropriate degree of adaptivity into the observation model. Without any adaptivity, tracking fails when object properties change, for example when illumination changes affect surface colour. Conversely, if an observation model adapts too readily then, during some transient failure of tracking, it is liable to adapt erroneously to some par...

This research project aims to use machine learning techniques to improve the performance of three-dimensional vision systems. Building on our earlier work, our approach represents and organizes models of object classes in a hierarchy of probabilistic concepts, and it uses Bayesian inference methods to focus attention , recognize objects in images, and make predictions about occluded parts. The ...

In the classical image-based visual servoing framework, error signals are directly computed from image feature parameters, allowing, in principle, control schemes to be obtained that need neither a complete three-dimensional (3D) model of the scene nor a perfect camera calibration. However, when the computation of control signals involves the interaction matrix, the current value of some 3D par...

In this article we present a cognitive approach to person tracking from a mobile platform. The core of the technique is a biologically inspired observation model that combines several feature channels in an object and background dependent way, in order to optimally separate the object from the background. This observation model can be learned quickly from a single training image and is easily a...