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PEVR: Pose Estimation for Vehicle Re-Identification

  • Saifullah TumraniEmail author
  • Zhiyi Deng
  • Abdullah Aman Khan
  • Waqar Ali
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11809)

Abstract

Re-identification is a challenging task because the available information is partial. This paper presents an approach to tackle vehicle re-identification (Re-id) problem. We focus on pose estimation for vehicles, which is an important module of vehicle Re-id. Person Re-id received huge attention, while vehicle re-id was ignored, but recently the computer vision community have started focusing on this topic and have tried to solve this problem by only using spatiotemporal information while neglecting the driving direction. The proposed technique is using visual features to find poses of the vehicle which helps to find driving directions. Experiments are conducted on publicly available datasets VeRi and CompCars, the proposed approach got excellent results.

Keywords

Vehicle re-identification Pose estimation Pose classifying model Machine learning 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Saifullah Tumrani
    • 1
    Email author
  • Zhiyi Deng
    • 1
  • Abdullah Aman Khan
    • 1
  • Waqar Ali
    • 1
    • 2
  1. 1.School of Computer Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengduChina
  2. 2.Faculty of Information TechnologyThe University of LahoreLahorePakistan

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