Pedestrian re-identification method based on self-excitation discriminative feature learning

Abstract

The invention discloses a pedestrian re-identification method based on self-excitation discriminative feature learning, which comprises the following steps: (1) selecting a pedestrian re-identification network, and adding a negative branch on the original network; (2) in the training stage, generating a classification loss function by the original network, generating a confrontation loss functionand a mutual exclusion response item between the original network and the negative branch to form an objective function, and utilizing a random gradient descent method to optimize the whole network; (3) in the test stage, removing a negative branch, only keeping the part, in front of the classifier, of the original network as a trained network model, and inputting a pedestrian picture for extracting a feature vector test; and (4) in the pedestrian retrieval stage, extracting the feature vector of each picture in the picture library by using the trained network model, and selecting the identityof the picture with the highest similarity with the feature vector of the to-be-queried pedestrian picture as a final recognition result. According to the invention, the effect of the existing pedestrian re-identification network can be improved.

Description

technical field [0001] The invention relates to the field of computer vision and pattern classification, in particular to a pedestrian re-identification method based on self-excited discriminative feature learning. Background technique [0002] In recent years, with the emergence of a large number of surveillance cameras in public places, pedestrian re-identification technology has received more and more attention. The goal of pedestrian re-identification technology is to perform cross-camera pedestrian search, that is, given a pedestrian picture captured by a certain camera, find pictures belonging to the same identity as this picture from other cameras. Pedestrian re-identification has a wide range of applications in missing person finding and suspect tracking. In recent years, pedestrian re-identification technology has developed rapidly, but there is still a long way to go before it can be applied to actual scenes. The difficulty is caused by many aspects: changes in il...

AI Technical Summary

Problems solved by technology

[0006] The present invention provides a pedestrian re-identification method based on self-excited discriminative feature learning, which solves the problem of insufficient optimization of the existing pedestrian feature learning network, and achieves better than traditional network optimization based on the existing model structure. way better results

Images