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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 throughdoi:10.5244/c.18.70 dblp:conf/bmvc/TownM04 fatcat:pzhj5zqajvhxtlq2f5iy36cs2q