Considering the problems of moving multi-target in video images, fuzzy edge features, and difficult target tracking, a kernel correlation filtering tracking algorithm based on edge features of multi-target video images is proposed in this paper. First, the time of 3 frame images of the target motion trajectory in video images is set as the linear segment. Then, the linear judgment method is used to capture the target. In addition, the dynamic edge evolution technology is used to accurately extract the edge features of the captured target; combined with the gradient angle histogram and color information of video images, the gradient angle-chroma saturation histogram color features are obtained, and the feature weight of the tracking target is obtained. Finally, the kernel correlation filtering tracking algorithm is used to realize the multi-target tracking of video images through cyclic shift, cyclic matrix, and ridge regression model-learning classifier. The experiment results show that the multi-target tracking success rate of the algorithm is above 99%, and the number of images that can be tracked per second is above 65 frames in the complex environment, such as size change, color change, and occlusion, which has superior tracking performance.