Sparse representation is one of effective methods in dealing with the moving object detection.However

the quickness and robustness of object detection are far from being solved in the existing methods.In this paper

a fast and robust moving object detection model based on the maximum posteriori probability is proposed

and a two-stage detection algorithms is designed.At the first stage

sparse coefficient is quickly solved by using coding transfer; At the second stage

based on spatial continuity structure

moving object detection is achieved by using graph cut.The experimental results on several challenging image sequences show that the proposed method has better performance than the existing classical moving object detection algorithms in rapidity and robustness.