Because of the rapid development of the convolutional neural network in recent years, the re-recognition of pedestrians has become another area of computer vision that is worthy of research after face recognition. The pedestrian re-recognition method involves verifying the similarity of two pedestrians or whether they are the same person and measuring the similarity of two features. And a pedestrian is a picture formed by multiple cameras, and its external conditions such as illumination, angle, and distance and it will increase the difficulty of verifying the similarities of two features. In this paper, a new method of pedestrian re-recognition based on combined Joint-Bayesian method and multi-camera shooting is proposed, which can effectively solve the problems caused by the change of shooting conditions of different cameras. Due to the good feature measurement ability of Joint-Bayesian, this paper studies a set of Joint-Bayesian matrices under different cameras, and combines with the global Joint Bayesian matrix to obtain a good recognition rate. On the Market-1501 and DukeMTMC-reID, the proposed method is used. The Rank-1 reached 88.09% and 80.07%, and the mAP reached 78.24% and 70.91%, which verified the effectiveness of the proposed method.