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Detection and Classification of Vehicle Types from Moving Backgrounds

  • Xuesong Le
  • Jun JoEmail author
  • Sakong Youngbo
  • Dejan Stantic
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 751)

Abstract

Using unmanned aerial vehicles (UAV) as devices for traffic data collection exhibits many advantages in collecting traffic information. This paper introduces a new vehicle dataset based on image data collected by UAV first. Then a novel learning framework for robust on-road vehicle recognition is presented. This framework starts with conventional supervised learning to create initial training data set. Then a tracking-based online learning approach is applied on consecutive frames to improve the accuracy of vehicle recogniser. Experimental results show that the proposed algorithm exhibits high accuracy in vehicle recognition at different UAV altitudes with different view scopes, which can be used in future traffic monitoring and control in metropolitan areas.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Xuesong Le
    • 1
  • Jun Jo
    • 1
    Email author
  • Sakong Youngbo
    • 2
  • Dejan Stantic
    • 1
  1. 1.School of Information and Communication TechnologyGriffith UniversitySouthportAustralia
  2. 2.SoletopDaejeonSouth Korea

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