Abstract: The target person recognition is a problem of person re-identification in multiple non-overlapping camera views. Existing target person recognition mostly extracts the human appearance feature, and re-identify target pedestrians through the feature similarity. For the pedestrians who have the most similar area and a small different part, these methods still can not give accurate recognition results. In this article, we consider that pedestrians of recognition are almost in a standing posture, and the vertical structure of the same pedestrian is more similar to the vertical structure of different pedestrians. Therefore, on the basis of densely patch-matching, we propose a matching method with spatial constraints(SCM),which not only considers the process of local patch matching in two different images, but also concerns the constraint of each patch in the vertical direction. In order to reduce the negative impact of background for identification, we adopt the method of pose evaluation to extract roughly foreground of the human body. In our experiment, the proposed approach have been tested in the most challenging public VIPeR database and CUHK02 database, and the results prove that it reaches the best recognition results so far.