In order to solve the problem that background model can not be well adapt to background changes in traditional single-Gaussian background model (SGM) detection, an innovative single-Gaussian background model detection method is proposed. N frames are used to establish the initial model, and the background area is obtained by frame difference method. At the same time, the background is divided into a large area of the stationary area, historic changing area and historic area of the changing one. Then the large stationary area and historic changing area are taken with fixed update rate and the relevant track area of historic changing area is taken with linear attenuation in accordance with the time distribution. So background model parameters are updated. The moving target is obtained by using the background subtraction. According to the experiment, the self-adaptability of the proposed algorithm model is improved greatly, and the detection of moving target is more accurate based on single Gaussian background model.