Cross-domain pedestrian re-identification method based on unsupervised joint multi-loss model

Abstract

The invention discloses a cross-domain pedestrian re-identification method based on an unsupervised joint multi-loss model. The method mainly solves the problem of low identification rate of an existing unsupervised cross-domain pedestrian re-identification method. The method comprises the following steps: 1) obtaining a data set, and dividing the data set into a training set and a test set; 2) carrying out a plurality of preprocessings and extensions on the training set; 3) selecting a residual network as a reference network model, initializing network parameters, and adjusting a network structure; 4) constructing a target domain loss function; 5) fusing the target domain loss function with the source domain loss function and the triple loss function to obtain a total loss function; 6) training the residual network by using the total loss function to obtain a trained network model; and 7) inputting the test set into the trained network model, and outputting an identification result. The identification rate of unsupervised cross-domain pedestrian re-identification is improved, the occurrence of an over-fitting situation is effectively avoided, and the method can be used for intelligent security of suspected target search and pedestrian cross-camera tracking.

Description

technical field [0001] The invention belongs to the field of computer vision and deep learning, and specifically relates to a cross-domain pedestrian re-identification method, which can be used in the intelligent security field of searching for suspicious targets and tracking pedestrians across cameras. Background technique [0002] With the construction of digital cities, surveillance videos are more and more widely used in various places where people live. These massive surveillance videos play a very important role in public security fields such as urban security and crime tracking. How to better process these data is also an important issue. Great challenges for our future. [0003] Person re-identification, also known as person re-identification, is a technology that uses computer vision technology to determine whether a specific pedestrian exists in an image or video sequence, and is widely considered as a sub-problem of image retrieval. Given a monitored pedestrian i...

AI Technical Summary

Problems solved by technology

Although this method has achieved good recognition results, due to ignoring the distribution of data featu

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