车辆再识别技术综述

刘凯; 李浥东; 林伟鹏

doi:10.11959/j.issn.2096-6652.202002

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车辆再识别技术综述

学术论文 | 更新时间：2024-06-05

- 车辆再识别技术综述
- A survey on vehicle re-identification
- 智能科学与技术学报 2020年2卷第1期页码：10-25
- 作者机构：
- 作者简介：
  
  [ "刘凯（1996- ），男，北京交通大学计算机与信息技术学院硕士生，主要研究方向为计算机视觉、车辆再识别" ]
  [ "李浥东（1982- ），男，博士，北京交通大学计算机与信息技术学院教授、副院长，主要研究方向为大数据分析与安全、隐私保护、智能交通等" ]
  [ "林伟鹏（1995- ），男，北京交通大学计算机与信息技术学院硕士生，主要研究方向为计算机视觉、车辆再识别" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61672088);国家自然科学基金资助项目;The National Natural Science Foundation of China(61790575)
- DOI：10.11959/j.issn.2096-6652.202002
  中图分类号： TP520
- 网络出版日期：2020-03，
  
  纸质出版日期：2020-03-20
- 稿件说明：
移动端阅览
刘凯, 李浥东, 林伟鹏. 车辆再识别技术综述[J]. 智能科学与技术学报, 2020,2(1):10-25.

Kai LIU, Yidong LI, Weipeng LIN. A survey on vehicle re-identification[J]. Chinese journal of intelligent science and technology, 2020, 2(1): 10-25.
刘凯, 李浥东, 林伟鹏. 车辆再识别技术综述[J]. 智能科学与技术学报, 2020,2(1):10-25. DOI： 10.11959/j.issn.2096-6652.202002.

Kai LIU, Yidong LI, Weipeng LIN. A survey on vehicle re-identification[J]. Chinese journal of intelligent science and technology, 2020, 2(1): 10-25. DOI： 10.11959/j.issn.2096-6652.202002.

摘要

车辆再识别是指给定一张车辆图像，找出其他摄像头拍摄的同一车辆，可将车辆再识别问题看作图像检索的子问题。在真实交通监控系统中，车辆再识别可以起到对目标车辆进行定位、监管、刑侦的作用。随着深度神经网络的兴起和大型数据集的提出，提升车辆再识别的准确度成为近年来计算机视觉和多媒体领域的研究热点。从不同角度对车辆再识别方法进行了分类，并从特征提取、方法设计和性能表现等方面对车辆再识别技术进行了概述、比较和分析，对车辆再识别技术面临的挑战及发展趋势进行了预测。

Abstract

Given a vehicle image

vehicle re-identification aims to find the same vehicle caught by other cameras

it can be regarded as a sub-problem of image retrieval.In the real traffic surveillance system

vehicle re-identification can play a role in locating

supervising and criminal investigation of target vehicles.With the rise of deep neural networks and the release of large-scale dataset

improving the accuracy and efficiency of vehicle re-identification has become a research focus in the field of computer vision and multimedia in recent years.The vehicle re-identification methods from different perspectives were classified

and the overview

comparison and analysis in terms of feature extraction

design and performance were given in detail

and the challenges and future trends of vehicle re-identification were predicted.

关键词

Keywords

references

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