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. The applications of the current system and recommendations for future research are also discussed.

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J. W. Jeon, D. H. Kim, B. Choi, G. Kim and Y. S. Kim, “A construction of vehicle image and ground truth database for developing vehicle maker and model recognitions,” International Journal of Technology and Engineering Studies, vol. 3, no. 6, pp. 229-235, 2017.