A vehicle re-identification method and device based on deep joint discriminant learning

Abstract

The embodiment of the present invention provides a vehicle re-identification and device based on deep joint discriminant learning. The method includes: building a system network architecture based on a deep convolutional neural network; performing an overall target loss function on the system network architecture through a video vehicle database Training, determining the parameters of the system network architecture; inputting the vehicle image to be recognized and the vehicle image within the effective geographical area into the system network architecture after the parameters are determined, extracting the feature vector of the image to be recognized and the The feature vector of the vehicle image within the effective geographical area, and compare the feature vector of the image to be recognized with the feature vector of the vehicle image within the effective geographical area, and search for the vehicle image within the effective geographical area A vehicle image having the highest similarity with the vehicle image to be recognized among the vehicle images. Through the embodiments of the present invention, the efficiency and accuracy of vehicle re-identification can be improved.

Description

technical field [0001] The invention belongs to the technical field of computer vision and intelligent transportation, and in particular relates to a vehicle re-identification method, device, terminal equipment and computer-readable medium based on deep joint discriminant learning. Background technique [0002] With the continuous development of artificial intelligence, computer vision and hardware technology, video image processing technology has been widely used in intelligent transportation systems (ITS). In recent years, with the promotion of highway video surveillance, image processing methods have begun to be applied to the field of traffic analysis, including traffic incident detection, traffic queue monitoring, vehicle type recognition, vehicle classification, traffic flow statistics, etc. Vehicle re-identification (Re-ID) is an important research direction in the field of computer vision, focusing on the recognition of specific target vehicles under cameras without ...

AI Technical Summary

Problems solved by technology

[0003] With the increasing amount of surveillance video data, relevant departments often need to search the massive video data when obtaining the required clues from these surveillance videos. However, the existing vehicle re-identification methods are too inefficient and have insufficient accuracy. high problem

For example, if the public security department needs to obtain the driving record of a suspected vehicle (unknown license plate number or license plate vehicle) within the past month, it needs to watch the surveillance video of the major streets and roads within the past month, and use the existing photos of the suspect vehicle , through the human eye or simple image matching method to identify the picture where the suspect vehicle is located, so as to summarize the driving track of the suspect vehicle. This kind of identification method of the suspect vehicle is too simple, and the recognition efficiency and accuracy are difficult to guarantee

Images