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Vehicle re-identification method based on multi-loss fusion model

A fusion model and re-recognition technology, applied in the field of computer vision, can solve problems such as complex training process, low accuracy rate, and poor re-recognition effect

Active Publication Date: 2020-07-07
NANJING UNIV OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing technology has technical problems such as complicated training process, poor re-identification effect, and low accuracy rate

Method used

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  • Vehicle re-identification method based on multi-loss fusion model
  • Vehicle re-identification method based on multi-loss fusion model
  • Vehicle re-identification method based on multi-loss fusion model

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Embodiment Construction

[0016] With the development of computer technology and information technology, the urban traffic monitoring system is gradually popularized, and the research on monitoring objects such as people, vehicles, roads, buildings, etc. has also attracted a lot of attention. In order to overcome the deficiencies of the prior art, the present invention provides a vehicle re-identification method based on a multi-loss fusion model.

[0017] Below in conjunction with accompanying drawing, the present invention will be further described.

[0018] refer to figure 1 , the specific steps of the present invention are further described in detail. In this implementation, the commonly used large-scale data set VehicleID is taken as an example to illustrate the training and testing process of the network model, and show related experimental results.

[0019] Step 1, preprocessing the vehicle image.

[0020] Read the original vehicle image data set, in which the data set is specifically divided ...

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Abstract

The invention discloses a vehicle re-identification method based on a multi-loss fusion model. According to the method, a deep convolutional neural network structure is designed for the problem of vehicle re-identification, a multi-loss fusion model is adopted to jointly supervise the training of the deep convolutional neural network, the joint optimization of the same ID sample difference and different ID sample differences of vehicles is realized, and the purpose of learning feature expression with higher discriminability is achieved. Wherein the proposed multi-cluster center loss function can increase the inter-class distance and shorten the intra-class distance, so that the vehicle features belonging to the same ID are close to the class center as much as possible, and the discrimination of feature expression is effectively improved. According to the multi-loss fusion model provided by the invention, multiple data enhancement modes are combined, so that the vehicle re-identification precision is effectively improved.

Description

technical field [0001] The invention belongs to the technical field of computer vision, in particular to a vehicle re-identification method based on a multi-loss fusion model. Background technique [0002] With the development of society, the use of vehicles in human life has become more and more common and important. Vehicle research has also received extensive attention, including applications in the field of computer vision, such as vehicle classification, vehicle detection, and vehicle re-identification. Among them, vehicle re-identification has many applications in video surveillance, public safety and intelligent transportation. [0003] Vehicle re-identification aims to identify target vehicles from multiple non-overlapping cameras in large-scale surveillance videos. Although the license plate information can be recognized, due to changes in perspective and environment, in most cases, it is difficult to accurately obtain all license plate information, which will cau...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04
CPCG06V20/54G06V2201/08G06N3/045G06F18/253G06F18/214Y02T10/40
Inventor 李旻先许诗瑞
Owner NANJING UNIV OF SCI & TECH
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