This paper reports on work which fuses three different appearance models to enable robust tracking of multiple objects on the basis of colour. Short-term variation in object colour is modelled non-parametrically using adaptive binning histograms. Appearance changes at intermediate time scales are represented by semi-parametric (Gaussian mixture) models while a parametric subspace method (Robust PCA) is employed to model long term stable appearance. Fusion of the three models is achieved through

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... particle filtering and the Democratic integration method. It is shown how robust estimation and adaptation of the models both individually and in combination results in improved visual tracking accuracy.