In view of the noise interference to video images and the complexity of background change, the traditional Census transform eigenvalue dependence on the central pixel is improved, and the Census template is established to maintain the robustness of the Census transform to light changes. A new background modeling method is established by combining the improved Census transform eigenvalue, image pixel value, update frequency, latest update time and dynamic index. The background texture difference is adaptively selected and fused with multiple features to update the background model. According to the dynamic index, the background change complexity is established, and different update rules are established to improve the stability of the model for light mutation and complex scene processing. After testing multiple sets of standard video sequences, the detection accuracy of this algorithm is better than that of other algorithms, which effectively improves the influence of light mutation on foreground target extraction, increases the robustness to light mutations and complex scenes, and reduces the false foreground caused by holes and pixel shift of the moving target.