The invention relates to a maximum-particle-size structure descriptor-based pedestrian re-identification method. The method comprises the following steps of S1, obtaining colorful pedestrian images in an image set, and processing the pedestrian images by using a Gabor filter to obtain a plurality of dimensional images; S2, obtaining color difference histograms (CDH) of the dimensional images, and extracting LMCC descriptors; S3, extracting LOMO descriptors; S4, performing measure learning by using an LDA algorithm to obtain optimal sub-space projection of a feature space; and S5, inputting to-be-identified pedestrian images, and calculating similarity measure distances between the to-be-identified pedestrian images and the pedestrian images in the image set to obtain an identification result. Compared with the prior art, the method has relatively good robustness for change of factors such as illumination, rotation, translation and the like, can be used for extracting essential features of the images, has good pedestrian identification performance, and is not sensitive to change of illumination, view angles, shielding and the like.