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

Joon Woo Jeon, Dong-Hyun Kim, Bumsuk Choi, Geonwoo Kim and Yoo-Sung Kim
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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

International Journal of Technology and Engineering Studies, 2017, vol. 3, issue 6, 229-235

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.

Keywords: Vehicle Database; Vehicle Maker and Model Classifier; Machine Learning; Video Annotation System; Ground Truth Data (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:apa:ijtess:2017:p:229-235

DOI: 10.20469/ijtes.3.40002-6

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