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A Construction of Vehicle Image and Ground Truth Database for Developing Vehicle Maker and Model Recognitions

Author

Listed:
  • JOON WOO JEON

    (Inha University, Incheon, South Korea)

  • DONG-HYUN KIM

    (Inha University, Incheon, South Korea)

  • BUMSUK CHOI

    (Electronics and Telecommunications Research Institute, Korea)

  • GEONWOO KIM

    (Electronics and Telecommunications Research Institute, Korea)

  • YOO-SUNG KIM

    (Inha University, Incheon, South Korea)

Abstract

In this paper, the construction process of the INHA Vehicle Database, which can be used for developing of a Vehicle Maker & Model (VMM) classifier, is introduced. In order to develop a vehicle detector and/or VMM classifier with the machine learning technology for the social security services or Intelligent Transportation Systems (ITS), a large volume of vehicle images and ground-truth data acquired from various surveillance cameras in real environments should be obtained. For such purpose, fixed CCTV cameras, dash-cams attached to operating vehicles, and smartphones are being utilized for recording vehicle videos. From these vehicle videos, about 11,855 vehicle images and ground-truth data are being created in a month using INHA-VAS (Video Annotation System) for the INHA Vehicle Database.

Suggested Citation

  • Joon Woo Jeon & Dong-Hyun Kim & Bumsuk Choi & Geonwoo Kim & Yoo-Sung Kim, 2017. "A Construction of Vehicle Image and Ground Truth Database for Developing Vehicle Maker and Model Recognitions," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 3(6), pages 229-235.
    • Handle: RePEc:apa:ijtess:2017:p:229-235
    DOI: 10.20469/ijtes.3.40002-6
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    References listed on IDEAS

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    1. Sutartip Wittayapiyanon & Sathaporn Chuepeng, 2017. "Sport utility vehicle seat structure simulation of frontal oblique crash," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 3(3), pages 69-78.
    2. Chao Hsi Huang & Min Hao Chang & I Hsuan Lin, 2016. "Research on Single-Board Computers Clustering the Computing Performance," International Journal of Technology and Engineering Studies, PROF.IR.DR.Mohid Jailani Mohd Nor, vol. 2(5), pages 125-133.
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