Pedestrian re-identification method based on clustering guidance and paired measurement triple loss

The invention discloses a pedestrian re-identification method based on cluster guidance and paired measurement triple loss. The method comprises the following steps: 1, acquiring a similarity matrix based on features output by a deep learning network and corresponding labels; 2, calculating sampling loss of hard cosine similarity measurementsamples in paired measurement; 3, calculating sampling loss of hard European style similarity measurement samples in the paired measurement; 4, calculating a clustering guidance correction term, and fusing all the losses to obtain clustering guidance and paired measurement triple losses; and 5, combining clustering guidance and paired measurement triple loss with cross entropy loss based on representation learning to obtain final loss, and adding the final loss into network parameter training for updating. According to the method, in combination with a paired measurement mode, a deep learning model can complementarily mine the similarity of the samples from different angle