The invention provides a cross-domain
pedestrian re-identification method and
system based on multi-feature mixed learning, and belongs to the technical field of
computer vision. The method comprises: by means of a re-identification model subjected to combined training, extracting
pedestrian global features,
pedestrian attribute features and pedestrian local features of the pedestrian image to be recognized and a bottom
library image, which is similar to the pedestrian identity in the pedestrian image to be recognized, in the image bottom
library gallley; and fusing the extracted to-be-identified features, and carrying out
similarity matching sorting on the fused features of the features of the bottom
library image to obtain a pedestrian re-identification result. According to the method, inter-domain joint training and multi-feature mixed learning are utilized to reduce inter-domain differences, so that the
system is more stable and higher in robustness, source domain training of global and local features and joint training of attribute features are performed on images of different scenes, pedestrian attributes are combined, the
adaptive capacity of a cross-domain pedestrian re-identification model is improved, and pedestrian re-identification is carried out on a cross-domain
data set, so that the cross-domain pedestrian re-identification performance is improved.