Cross-domain pedestrian re-identification method and system fusing multiple source domains

Abstract

The invention discloses a cross-domain pedestrian re-identification method and system fusing multiple source domains. The method comprises the steps that when a cross-domain pedestrian re-identification model is trained, multiple source domain data sets are obtained, the cross-domain pedestrian re-identification model is trained by training a representation learning network and a metric learning network through one source domain data set, the trained cross-domain pedestrian re-identification model is obtained, and when pedestrian re-identification is conducted, a pedestrian sample pair to be identified is inputted into the trained cross-domain pedestrian re-identification model to obtain a pedestrian re-identification result. By adopting the method and the system, the data of the pluralityof the source domains are fused in the training process, the feature representation of the pedestrian can be better learned, and compared with a single training model, the pedestrian re-identification accuracy can be improved, and the problem that the model performance is reduced due to inter-domain difference is effectively solved.

Description

technical field [0001] The present invention relates to the technical field of pedestrian re-identification, in particular to a cross-domain pedestrian re-identification method and system that integrates multiple source domains. Background technique [0002] Person re-identification (Person re-identification), also known as pedestrian re-identification, is a technology that uses computer vision technology to determine whether a specific pedestrian exists in an image or video sequence. In recent years, due to the rapid development of deep learning, the performance of pedestrian re-identification algorithms has also been improved unprecedentedly. When implementing a person re-identification system based on deep learning, when the model trained by a single training set is applied to the actual scene, the performance decline is very obvious, because when the trained model is directly used in the real scene, often Because of the inter-domain differences between the pedestrians i...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a cross-domain pedestrian re-identification method and system that integrates multiple source domains, which can effectively solve the problem of model performance degradation caused by inter-domain differences and improve the accuracy of pedestrian re-identification

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