The invention relates to a pedestrian re-identification method based on human skeleton mutual learning, which comprises the following steps: (1) estimating pedestrian postures and skeletons by adopting a bottom-to-top method, marking articulation points of pedestrians in the process, carrying out local segmentation on the pedestrians by using an articulation point segmentation method, and executing local block matching; (2) estimating the joint point distance on the basis of a pedestrian 2D skeleton through a bottom-up method to learn global skeleton information, and executing global skeletonmatching; and (3) mutual learning is carried out by adopting biological feature-based local block matching and overall skeleton matching, classification loss and measurement loss are trained respectively, and the obtained mutual learning loss is shared in global feature matching to serve as priori experience to guide and correct global matching errors. Compared with the prior art, the method has the advantages of few influence factors, improved local matching accuracy, higher recognition accuracy and the like.