Aiming at the defect that the traditional moving objects detection（ MOD） algorithm based on Gaussian mixture model（ GMM） has poor anti-noise performance

sensitive to dynamic background interference

a Gaussian mixture modeling combined with Markov random field（ MRF） moving target detection method. Firstly

the video image is modeled by GMM

and foreground target area is initially marked. The original image is decomposed into superpixels. According to foreground image extracted by GMM

the probabilistic superpixel images is obtained. MRF modeling is used to model the probabilistic superpixel images and to obtain the final foreground image of moving target. The comparison analysis of the final experiments show that the proposed algorithm can get better results than traditional algorithms for complex scenes such as noise interference and dynamic disturbance background.