자율 주차 시스템을 위한 실시간 차량 추출 알고리즘

A Real-time Vehicle Localization Algorithm for Autonomous Parking System

  • 한종우 (한국기술교육대학교 컴퓨터공학부) ;
  • 최영규 (한국기술교육대학교 컴퓨터공학부)
  • Hahn, Jong-Woo (Korea University of Technology and Education, School of Computer Science and Engineering) ;
  • Choi, Young-Kyu (Korea University of Technology and Education, School of Computer Science and Engineering)
  • 투고 : 2011.05.04
  • 심사 : 2011.05.31
  • 발행 : 2011.06.30

초록

This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.

키워드

참고문헌

  1. C. Wren, A. Azarbayejani, T. Darrell, and A. Pentland, "Pfinder: Real-Time Tracking of the Human Body," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 780-785, July 1997. https://doi.org/10.1109/34.598236
  2. C. Stauffer and W. Grimson, "Adaptive Background Mixture Models for Real-Time Tracking," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 246-252, 1999.
  3. P. KaewTraKulPong and R. Bowden, "An Improved Adaptive Background Mixture Model for Real-Time Tracking with Shadow Detection," Proc. European Workshop Advanced Video Based Surveillance Systems, 2001.
  4. Z. Zivkovic, "Improved Adaptive Gaussian Mixture Model for Background Subtraction," Proc. Intl Conf. Pattern Recognition, vol. 2, pp. 28-31, 2004.
  5. Q. Zang and R. Klette, "Robust Background Subtraction and Maintenance," Proc. Intl Conf. Pattern Recognition, vol. 2, pp. 90-93, 2004.
  6. A. Elgammal, R. Duraiswami, D. Harwood, and L.S. Davis, "Background and Foreground Modeling Using Nonparametric Kernel Density Estimation for Visual Surveillance," Proc. IEEE, vol. 90, no. 7, pp. 1151-1163, 2002.
  7. K. Kim, T. Chalidabhongse, D. Harwood, and L. Davis, "Background Modeling and Subtraction by Codebook Construction," Proc. IEEE International Conf. Image Processing, vol. 5, pp. 3061-3064, 2004.
  8. M. Heikkila and M. Pietikainen, "A Texture-Based Method for Modeling the Background and Detecting Moving Objects," IEEE Trans. on PAMI, Vol. 28, No. 4, pp. 657-662, April 2006.
  9. G. Zhao and M. Pietikäinen, "Dynamic texture recognition using local binary patterns with an application to facial expressions," IEEE Trans. on PAMI, Vol. 29, No. 6, pp. 915-928, 2007.
  10. 최영규, 이영무, "대각선형 지역적 이진패턴을 이용한 성별 분류 방법에 대한 연구," 반도체및디스플레이장비학회지 제8권 제3호, pp. 39-44, 2009.
  11. M. Xiao, C. Han and L. Zhang, "Moving Shadow Detection and Removal for Traffic Sequences," International Journal of Automation and Computing, 04(1), pp. 38-46, 2007. https://doi.org/10.1007/s11633-007-0038-z
  12. Y. Sonoda, T. Ogata. "Separation of Moving Objects and Their Shadows, and Application to Tracking of Loci in the Monitoring Images," In Proceedings of 1998 Fourth International Conference on Signal Processing, Beijing, China, vol. 2, pp. 1261-1264, 1998.
  13. T. N. Tan, G. D. Sullivan, and K. D. Baker, "Model-based localization and recognition of road vehicles," Int. J. Comput. Vis., vol. 27, no. 1, pp. 5-25, 1998. https://doi.org/10.1023/A:1007924428535
  14. J. Lou, T. Tan, W. Hu, H. Yang, and S. J. Maybank. "3-d model-based vehicle tracking," IEEE Transactions on Image Processing, 14(10):1561-1569, Oct 2005. https://doi.org/10.1109/TIP.2005.854495
  15. B. Barrois, S. Hristova, C. Wohler, F. Kummert and C. Hermes, "3D pose estimation of vehicles using a stereo camera "Intelligent Vehicles Symposium, 2009 IEEE , pp. 267-272.
  16. P. J. Besl and N. D. McKay, "A method for registration of 3-d shapes," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239-256, February 1992. https://doi.org/10.1109/34.121791