This paper proposed an adaptive background model for motion detection based on statistic information of probabilities. The approach can select thresholds of foreground and background adaptively and adapt to different scenes without training samples and human concerned. By using statistic information of historical pixels to update background can deal with moved/inserted objects in background. Meanwhile

a background model updated according to statistical characteristic is also provided in this paper. It gets ideal background and good detection results. Experimental results demonstrate the proposed algorithms can get relative good background and improve detection results for different scenes.