MULTI-FEATURE STEREO VISION SYSTEM FOR ROAD TRAFFIC ANALYSIS

Quentin Houben, Juan Carlos Tocino Diaz, Nadine Warzée, Olivier Debeir, Jacek Czyz

Abstract

This paper presents a method for counting and classifying vehicles on motorway. The system is based on a multi-camera system fixed over the road. Different features (maximum phase congruency and edges) are detected on the two images and matched together with local matching algorithm. The resulting 3D points cloud is processed by maximum spanning tree clustering algorithm to group the points into vehicle objects. Bounding boxes are defined for each detected object, giving an approximation of the vehicles 3D sizes. A complementary 2D quadrilateral detector has been developed to enhance the probability of matching features on vehicle exhibiting little texture such as long vehicles. The algorithm presented here was validated manually and gives 90% of good detection accuracy.

References

  1. Boykov, Y., Veksler, O., and Zabih, R. (2001). Fast approximate energy minimization via graph cuts. PAMI, 23(11).
  2. Dickinson, K. and Wan, C. (1989). Road traffic monitoring using the trip ii system. In IEE Second International Conference on Road Traffic Monitoring. The MIT Press TODO check.
  3. Gibson, D., FHWA, Tweedy, C., and Corp., O. (1998). An advanced preformed inductive loop sensor. In North American Travel Monitoring Exhibition and Conference(NATMEC).
  4. Hartley, R. and Zisserman, A. (2004). Multiple view geometry in computer vision. Cambridge University Press, second edition.
  5. Hogg, D., Sullivan, G., Baker, K., and Mott, D. (1984). Recognition of vehicles in traffic scenes using geometric models. In Proceedings of the International Conference on Road Traffic Data Collection, London. IEE.
  6. Kastrinaki, V., Zervakis, M., and Kalaitzakis, K. (2003). A survey of video processing techniques for traffic applications. In Image and Vision Computing 21. Elsevier.
  7. Kim, J., Lee, K., Choi, B., and Lee, S. (2005). A dense stereo matching using two-pass dynamic programming with generalized ground control points. IEEE CVPR, 2:1075-1082.
  8. Kovesi, P. (1999). Image features from phase congruency. Videre: Journal of Computer Vision Research.
  9. Lourenco, A., Freitas, P., Ribeiroy, M. I., and Marquesy, J. S. (2002). Detection and classification of 3d moving objects.
  10. Ohta, Y. and Kanade, T. (1985). Stereo by intea nad interscanline search using dynamic programming. PAMI.
  11. Scharstein, D. and Szeliski, R. (2002). a taxonomy and evaluation of dense two-frame stereo correspondence algorithms. In Intl Journal of Computer Vision, vol. 47,no. 1, pp. 742.
  12. Tan, X.-J., Li, J., and Liu, C. (2007). A video-based real-time vehicle detection method by classified background learning. World Transactions on Engineering and Technology Education, 6(1).
  13. Viola, P. and Jones, M. (2004). Robust real-time object detection. International Journal of Computer Vision.
  14. Yang, Q., Wang, L., and Yang, R. (2006). Real-time global stereo matching using hierarchical belief propagation. In BMVC06, page III:989.
  15. Zhang, Z. (1998). Determining the epipolar geometry and its uncertainty: A review. IJCV, 27(2):161195.
  16. Zhang, Z. (2000). Determining the epipolar geometry and its uncertainty. IEEE TPAMI, 22:13301334.
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Paper Citation


in Harvard Style

Houben Q., Carlos Tocino Diaz J., Warzée N., Debeir O. and Czyz J. (2009). MULTI-FEATURE STEREO VISION SYSTEM FOR ROAD TRAFFIC ANALYSIS . In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 554-559. DOI: 10.5220/0001803405540559


in Bibtex Style

@conference{visapp09,
author={Quentin Houben and Juan Carlos Tocino Diaz and Nadine Warzée and Olivier Debeir and Jacek Czyz},
title={MULTI-FEATURE STEREO VISION SYSTEM FOR ROAD TRAFFIC ANALYSIS},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={554-559},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001803405540559},
isbn={978-989-8111-69-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)
TI - MULTI-FEATURE STEREO VISION SYSTEM FOR ROAD TRAFFIC ANALYSIS
SN - 978-989-8111-69-2
AU - Houben Q.
AU - Carlos Tocino Diaz J.
AU - Warzée N.
AU - Debeir O.
AU - Czyz J.
PY - 2009
SP - 554
EP - 559
DO - 10.5220/0001803405540559