Object Recognition using Coloured

This paper describes an extension of a technique for the recognition and tracking of every day objects in cluttered scenes. The goal is to build a system in which ordinary desktop objects serve as physical icons in a vision based system for man-machine interaction. In such a system, the manipulation of objects replaces user commands. A view-variant recognition technique, developed by the second author, has been adapted by the rst author for a problem of recognising and tracking objects on a cluttered background in the presence of occlusions. This method is based on sampling a local appearance function at discrete viewpoints by projecting it onto a vector of receptive elds which have been normalised to local scale and orientation. This paper reports on the experimental validation of the approach, and of its extension to the use of receptive elds based on colour. The experimental results indicate that the second author's technique does indeed provide a method for building a fast and robust recognition technique. Furthermore, the extension to coloured receptive elds provides a greater degree of local discrimination and an enhanced robustness to variable background conditions. The approach is suitable for the recognition of general objects as physical icons in an augmented reality.