DOI QR코드

DOI QR Code

Real Time On-Road Vehicle Detection with Low-Level Visual Features and Boosted Cascade of Haar-Like Features

미약한 시각 특징과 Haar 유사 특징들의 강화 연결에 의한 도로 상의 실 시간 차량 검출

  • Received : 2010.11.25
  • Accepted : 2010.12.23
  • Published : 2011.01.01

Abstract

This paper presents a real- time detection of on-road succeeding vehicles based on low level edge features and a boosted cascade of Haar-like features. At first, the candidate vehicle location in an image is found by low level horizontal edge and symmetry characteristic of vehicle. Then a boosted cascade of the Haar-like features is applied to the initial hypothesized vehicle location to extract the refined vehicle location. The initial hypothesis generation using simple edge features speeds up the whole detection process and the application of a trained cascade on the hypothesized location increases the accuracy of the detection process. Experimental results on real world road scenario with processing speed of up to 27 frames per second for $720{\times}480$ pixel images are presented.

Keywords

References

  1. C. Tzomakas and W. Sleen, “Vehicle detection in traffic scenes using shadows,” Technical Report 98-06, Institut fur Neuroinformatik, Ruth-Universitat, Bochum, Germany, 1998.
  2. T. Zielke, M. Brauckmann, and W. von Seelen, “Intensity and edge based symmetry detection with application to carfollowing,” CVGIP:Image Understanding, vol. 58, pp. 177-190, 1993. https://doi.org/10.1006/ciun.1993.1037
  3. N. Matthews, P. E. An, D. Charnley, and C. J. Harris, “Vehicle detection and recognition in greyscale imagery,” Control Eng. Practice, vol. 4, pp. 473-479, 1996. https://doi.org/10.1016/0967-0661(96)00028-7
  4. Z. Sun, R. Miller, G. Bebis, and D. DiMeo, “A real-time precrash vehicle detection system,” Proc. of IEEE Intn’l Workshop Application of Computer Vision, Dec. 2002.
  5. P. Viola and M. Jones, “Rapid object detection using a boosted cascade of simple features,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2001.
  6. H. Bai, J. Wu, and C. Liu, “Motion and Haar-like feature based vehicle detection,” Proc. of the 12th International Multi-Media Modelling Conference, pp. 356-359, 2006.
  7. P. Viola and M. Jones, “Robust real-time face detection,” International Journal of Computer Vision, vol. 57, no. 2, pp. 137-154, 2004. https://doi.org/10.1023/B:VISI.0000013087.49260.fb
  8. P. Viola, M. Jones, and D. Snow, “Detecting pedestrians using patterns of motion and appearance,” Proc. of Ninth IEEE International Conference on Computer Vision, 2003.
  9. R. E. Schapire and Y. Singer, “Improved boosting algorithms using confidence-rated predictions,” Machine Learning, vol. 37, pp. 297-336, 1999. https://doi.org/10.1023/A:1007614523901
  10. S. P. Adhikari, H. Cho, H. Yoo, C. Yang, and H. Kim, “Onroad succeeding vehicle detection using characteristic visual features,” Trans. on KIEE, vol. 59, no. 3, 2010.
  11. 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, 2008. https://doi.org/10.1177/0278364908092131