A gait recognition method based on a generative adversarial network

The invention discloses a gait recognition method based on a generative adversarial network, and the method comprises the steps: carrying out the training based on an improved generative adversarial network through employing a reverse rebroadcast algorithm in a feature extraction stage, and obtaining a multi-field conversion model which can carry out the conversion among a plurality of different types of images; in the Gait recognition phase, Firstly, gait videos in a test set and a verification set are converted into gait energy graphs, then the gait energy graphs of test samples are converted into gait energy graphs consistent with a state domain and a visual angle domain in the verification set through the multi-field conversion model, and an identification result is obtained by comparing the similarity between the test samples and all verification samples. According to the method, three interference factors of view angles, clothes and carried objects can be processed at the same time, high robustness is a