Chinese Journal of Intelligent Science and Technology ›› 2020, Vol. 2 ›› Issue (1): 10-25.doi: 10.11959/j.issn.2096-6652.202002

• Regular Papers • Previous Articles     Next Articles

A survey on vehicle re-identification

Kai LIU,Yidong LI(),Weipeng LIN   

  1. School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China
  • Revised:2020-02-18 Online:2020-03-20 Published:2020-04-10
  • Supported by:
    The National Natural Science Foundation of China(61672088);The National Natural Science Foundation of China(61790575)

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.

Key words: vehicle re-identification, deep learning, feature representation, metric learning

CLC Number: 

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