Transactions of the Korean Society of Automotive Engineers (한국자동차공학회논문집)

The Korean Society of Automotive Engineers (한국자동차공학회)
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A Study on the Image DB Construction for the Multi-function Front Looking Camera System Development

다기능 전방 카메라 개발을 위한 영상 DB 구축 방법에 관한 연구

  • 기석철 (충북대학교 스마트카연구센터)
  • Received : 2017.01.02
  • Accepted : 2017.02.01
  • Published : 2017.03.01
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Abstract

This paper addresses the effective and quantitative image DB construction for the development of front looking camera systems. The automotive industry has expanded the capability of front camera solutions that will help ADAS(Advanced Driver Assistance System) applications targeting Euro NCAP function requirements. These safety functions include AEB(Autonomous Emergency Braking), TSR(Traffic Signal Recognition), LDW(Lane Departure Warning) and FCW(Forward Collision Warning). In order to guarantee real road safety performance, the driving image DB logged under various real road conditions should be used to train core object classifiers and verify the function performance of the camera system. However, the driving image DB would entail an invalid and time consuming task without proper guidelines. The standard working procedures and design factors required for each step to build an effective image DB for reliable automotive front looking camera systems are proposed.

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References

  1. Euro NCAP 2020 Roadmap Revision 1, http://www.euroncap.com/en/for-engineers/technical-papers/, 2015.
  2. The KITTI Vision Benchmark Suite, http://www.cvlibs.net/datasets/kitti/, 2016.
  3. The German Traffic Sign Recognition Benchmark, http://benchmark.ini.rub.de/?section=gtsrb&subsection=dataset, 2015.
  4. Daimler Pedestrian Benchmark Dataset, http://www.gavrila.net/Datasets/Daimler_Pedestrian_Benchmark_D/daimler_pedestrian_benchmark_d.html, 2013.
  5. K. Kim, "A Method of Establish DB to Use Mono Camera based Lane Detection & Vehicle Detection," IEIE Annual Conference Proceedings, pp.579-582, 2012.
  6. On Semiconductor, Automotive Application, http://www.onsemi.com/PowerSolutions/appDiagram.do?appId=131, 2016.
  7. Omnivision, Applications, Automotive Imaging, http://www.ovt.com/applications/application.php?id=7, 2016.
  8. H. J. Noh, J. W. Lee, D. J. Lim and J. K. Lee, "The Research of Constructing the Real-world Image Data Base for Verifying the Function and Recognition Rate of ADAS Based on Image Sensor," KSAE Annual Conference Proceedings, pp.1398-1402, 2012.
  9. H. J. Noh, J. W. Lee, D. J. Lim and J. K. Lee, "The Research of Constructing and Operating the Real-world Image Data Base for Verifying the Recognition Rate of ADAS Based Image Sensor," KSAE Annual Conference Proceedings, p.1095, 2013.
  10. Convention on Road Signs and Signals, http://www.unece.org/fileadmin/DAM/trans/conventn/signalse.pdf, 1995.