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\paragraph{}
Being able to segment a picture with two layers, one containing the objects of interest and the other one the background, is a problem that have been discussed about for more than one decade now. Its applications are wide but, recently, they are more focused on using those segmented part of the pictures so as to recognise an object in robotics vision or to reconstruct of tridimensional representation of the segmented area.

\paragraph{}
In the current paper, we propose a method to segment a foreground area assuming that the background stays still. However the illumination will stay unknown and the structure of the background will be learnt from a sequence of frames leading to a Global Mixture Model (GMM) and a local per pixel model. Eventually, the foreground area will be delimited thanks to a graph min-cut algorithm.

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