In order to realize the high precision moving object detection in snowy weather condition, this paper improves the GMM algorithm. Firstly, the multi-resolution, high and low threshold concepts are used to optimize the detection results, which can overcome the influence of the dynamic background noise. Then, the color model is used to suppress the weak shadows and illumination changes by moving objects. Finally, the hole is filled in the rectangle with the minimum constraint of each object, and the motion mask is filled due to the excessive suppression of the shadow and the loss of the surface covered by snow. Experimental results show that the improved algorithm is better than the GMM algorithm for all of the seven indicators. Compared with the current outstanding algorithm FTSG, there are four of the seven transcend, the two close.