The continuous research on panoramic vision in the field of vision shows that the accuracy of moving object detection based on image sequence obtained by fisheye lens is low,and the robustness is not high when disturbed by noise.Aiming at the above problems,an improved method of moving object detection based on panoramic vision is proposed.Firstly,the algorithm uses the five-frame difference method to process the image,and uses the difference between adjacent five frames to separate the foreground from the background,thus effectively reducing the target-hole problem.Then,the ghost phenomenon in detection is effectively overcome by improving the adaptive learning rate and updating the number of Gaussian distribution in the Gaussian mixture model.Finally,the target result is obtained by morphological processing.Experiments show that the improved algorithm provides more reliable detection results than the traditional panoramic image moving target detection does,and the target detection rate is higher.