The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
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On-Road Succeeding Vehicle Detection using Characteristic Visual Features

시각적 특징들을 이용한 도로 상의 후방 추종 차량 인식

  • 샴 아디카리 (전북대학교 전자정보공학부) ;
  • 조휘택 (전남대학교 문화사회과학 대학원) ;
  • 유현중 (상명대학교 정보통신공학과) ;
  • 양창주 (전북대학교 전자정보공학부) ;
  • 김형석 (전북대학교 전자정보공학부)
  • Published : 2010.03.01
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Abstract

A method for the detection of on-road succeeding vehicles using visual characteristic features like horizontal edges, shadow, symmetry and intensity is proposed. The proposed method uses the prominent horizontal edges along with the shadow under the vehicle to generate an initial estimate of the vehicle-road surface contact. Fast symmetry detection, utilizing the edge pixels, is then performed to detect the presence of vertically symmetric object, possibly vehicle, in the region above the initially estimated vehicle-road surface contact. A window defined by the horizontal and the vertical line obtained from above along with local perspective information provides a narrow region for the final search of the vehicle. A bounding box around the vehicle is extracted from the horizontal edges, symmetry histogram and a proposed squared difference of intensity measure. Experiments have been performed on natural traffic scenes obtained from a camera mounted on the side view mirror of a host vehicle demonstrate good and reliable performance of the proposed method.

Keywords

References

  1. M. Bertozzi, A.Broggi,and A. Fascoili," Vision-Based Intelligent Vehicles: State of the Art and Perspectives", Robotics and Autonomous Systems, vol.32, pp.1-16, 2000. https://doi.org/10.1016/S0921-8890(99)00125-6
  2. C. Tzomakas and W. Sleen,"Vehicle Detection in Traffic Scenes Using Shadows", Technical Report 98-06, Institut fur Neuroinformatik, Ruth-Universitat, Bochum, Germany, 1998
  3. T. Zielke, M. Brauckmann, and W. von Seelen, "Intensity and Edge Based Symmetry Detection with Application to Car-Following", CVGIP: Image Understanding, vol.58, pp.177-190, 1993 https://doi.org/10.1006/ciun.1993.1037
  4. N. Matthews, P. E. An, D. Charnley and C. J. Harris," Vehicle Detection and Recognition in Greyscale Imagery", Control Eng. Practice, vol.4, pp473-479, 1996 https://doi.org/10.1016/0967-0661(96)00028-7
  5. N. Srinivasa, "A Vision-Based Vehicle Detection and Tracking Method for Forward collision Warning", Proc. IEEE Intelligent Vehicle Symp., pp.626-631, 2002
  6. Z. Sun, R. Miller, G. Bebis and D. DiMeo, "A Real-Time Pre-crash Vehicle Detection system", Proc. IEEE Intn'l Workshop Application of Computer Vision, Dec. 2002
  7. C. Hoffman, "Fusing Multiple Features for Vehicle Detection", Intelligent Vehicle Symposium. pp.406-411,2006
  8. K. H. Lim, L.M. Ang, K. P. Seng and S. W. Chin, Lane-Vehicle Detection and Tracking", Proc. Intn'l Multi conference of Engineers and computer Scientists, vol2, 2009
  9. G. Zhao and S. Yuta ,"Obstacle Detection by Vision System for Autonomous Vehicle," Intelligent Vehicles, pp.31-36,1993
  10. M. Bertozzi and A. Broggi, "Vision-Based Vehicle Guidance," Computer, vol.30,no7,pp.49-55,July1997
  11. M. Bertozzi, A. Broggi, and A. Fascioli, "Obstacle and Lane Detection on Argo Autonomous Vehicle," IEEE Intelligent Transportation Systems, 1997
  12. A. Giachetti, M. Campani, and V. Torre, "The Use of Optical Flow for Road Navigation," IEEE Trans. Robotics and Automation, vol.14,no.1, pp.34-48, 1998 https://doi.org/10.1109/70.660838
  13. W. Kruger, W. Enkelmann, and S. Rossle, "Real-Time Estimation and Tracking of Optical Flow Vectors for Obstacle Detection," Proc. IEEE Intelligent Vehicle Symp., pp. 304-309, 1995
  14. Z. Sun, G. Bebis, and R. Miller,"On-Road Vehicle Detection: A Review", IEEE Transactions on Pattren Analysis and Machine Intelligence, vol.28, pp.694-711,2006 https://doi.org/10.1109/TPAMI.2006.104
  15. G. Marola, "Using Symmetry for Detecting and Locating Objects in a Picture," Computer Vision, Graphics, and Image Processing, vol.46, pp.179-195, 1989 https://doi.org/10.1016/0734-189X(89)90168-0
  16. W. H. Li, A. M. Zhang and , L. Kleeman, "Bilateral Symmetry Detection for Real-time Robotics Applications", The International Journal of Robotics Research, vol.27 no.7, pp.785-814, July2008 https://doi.org/10.1177/0278364908092131