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Local illumination changes due to shadows often reduce the quality of object-based video composition and mislead object recognition. This problem makes shadow detection a desirable tool for a wide range of applications, such as video production and visual surveillance. In this paper, an algorithm for the isolation of video objects from the local illumination changes they generate in real world sequences when camera, illumination and the scene characteristics are not known is presented. The algorithm combines a change detector and a shadow detector with a spatio-temporal verification stage. Colour information and spatio-temporal constraints are embedded to define the overall algorithm. Colour information is exploited in a selective way. First, relevant areas to analyse are identified in each image. Then, the colour components that carry most of the needed information are selected. Finally, spatial and temporal constraints are used to verify the results of the colour analysis. The proposed algorithm is demonstrated on both indoor and outdoor video sequences. Moreover, performance comparisons show that the proposed algorithm outperforms state-of-the-art methods.