A precise background detection is required for video surveillance applications in order to detect foreground objects. However, in the presence of cluttered scenes, standard techniques for background segmentation can fail. In this work we present a new technique for foreground detection that is able to detect the correct background in complex scenes. It works grouping neighbour pixels that fulfill some kind of spatial and temporal criteria. Spatial criterion is based on the appearance similarity of neighbour pixels while temporal criterion looks for the best temporal correlation in the whole video sequence. Initially, a set of seed points of the image are selected and both criteria are applied in an alternate way until all the pixels of the image have been visited and their background value has been calculated.
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