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Hierarchical and Spatial-colorimetric Model to Detect Moving Targets

Background subtraction is often one of the first tasks involved in video surveillance applications. Classical methods only use temporal modelling of the background pixels. Using pixel blocks with fixed size allows robust detection but these approaches lead to a loss of precision. We propose in this paper a model of the scene which combines a temporal and local model with a spatial model. This whole representation of the scene both models fixed elements (background) and mobile ones. This allows improving detection accuracy by transforming the detection problem in a two classes classification problem.