Vehicle re-identification method using weak supervision area recommendation

Abstract

The invention discloses a vehicle re-identification method and system using weak supervision area recommendation, and the method comprises the steps: collecting vehicle image data captured by a road monitoring camera, carrying out the data enhancement of the vehicle image data, and applying the data to a weak supervision area recommendation network designed in the invention; designing the structure of a weak supervision region recommendation network model, and optimizing a region recommendation module by using classification loss and region suggestion loss functions, so that a multi-scale local region with rich information degree in an image can be extracted, and local region features with higher discrimination and description are obtained, and the local features and the global features are optimized by using triple loss, so that the identification capability of the network is enhanced; and using an adaptive gradient descent algorithm to supervise the training of the weakly supervised region recommendation network in an end-to-end manner, after a trained model is obtained, calculating the similarity between the vehicle query set and the image library set, and sorting according to the similarity to obtain a vehicle re-identification result.

Description

Technical field [0001] The present invention belongs to the field of vehicle reinacity, and more particularly to a vehicle re-identification method recommended by the weak supervision region. Background technique [0002] With the continuous improvement of the living standards of the people, the number of motor vehicles in the city has increased dramatically, and the automobile plays an indispensable role in the production and life of the people. However, the car is in place for people to live, and many traffic safety issues are also inevitably brought, such as illegal violations and escapes. Intelligent urban management is an important measure to ensure urban security, while vehicles reinceptory is the basis and important components of such intelligent visual monitoring. Vehicle Recognition Technology refers to a vehicle image, which identifies the same identity from a video surveillance system of non-overlapping perspectives. By matching all the vehicles captured by the target ...

AI Technical Summary

Problems solved by technology

However, the acquisition of local features often relies on rich vehicle fine-grained labeling information. The number of vehicles in the city is as high as one million. The acquisition of rich labeling information means high costs. The application of the

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