Aiming at the problems of ghosts, shadows, and false detections occur when traditional ViBe algorithm detects moving targets in complex backgrounds, an improved ViBe moving target detection algorithm was proposed, which was called GS-ViBe algorithm. In the initialization stage of GS-ViBe background model, the maximum posteriori estimation method was used to determine the optimal number of Gaussian distributions of each pixel to form a multi-frame fusion background instead of single-frame background initialization method of ViBe, so that the ghosts were eliminated. In the GS-ViBe foreground detection stage, the multi-feature fusion shadow detection process was added, and the detection results were fused with ViBe foreground targets to obtain the foreground targets after eliminating shadows. Finally, in the GS-ViBe background model update stage, a dynamic update factor was introduced instead of a fixed update factor, so that the background could be updated adaptively, thereby reducing the false detection rate of targets. In comparison with traditional ViBe algorithm in a variety of complex backgrounds, it is found that the recall rate of GS-ViBe algorithm is increased by 37.74% on average, the accuracy rate is increased by 19.83% on average and the false detection rate is reduced by 52.57% on average. It shows that the GS-ViBe algorithm can effectively eliminate the interference from ghosts, shadows and false detections, which obtains the complete foreground targets.