Person re-identification method that combines random batch mask and multi-scale expression learning

摘要

PROBLEM TO BE SOLVED: To provide a person reidentification method in which a random batch mask and multi-scale expression learning are fused. SOLUTION: The person re-identification method includes a step of constructing a person re-identification training network, a step of adjusting network hyper-parameters with preset training parameters to obtain a learning network, and multi-scale expression learning and a random batch mask. The steps to block the branch, get the test network, enter the test set into the test network to get the corresponding test identification result, and determine if the accuracy rate of the test identification result is greater than or equal to a given value. If YES, the actual data set is input to the training network, otherwise the steps to retrain the network, block multiscale representation learning and random batch mask branches, obtain the application network, and apply the query image to the application network. To provide a step of inputting to and obtaining the corresponding identification result. [Selection diagram] Fig. 1