Abstract
A novel algorithm capable of estimating the profile of the road surface along the cameraviewing direction is proposed. When a disparity map from stereo matching is given, the algorithm estimates the profile precisely by applying the Dijkstra algorithm to a v-disparity representation. Although the road surface is very changeable, many algorithms of road scene analysis have relied on flatroad assumption or have estimated the profile roughly. The combination of the Dijkstra algorithm and a v-disparity representation contributes to eliminating such assumption and limit. We demonstrated the validity of the proposed algorithm by performing experiments with many road images.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
F. Oniga and S. Nedevschi, “Processing dense stereo data using elevation maps: road surface, traffic isle, and obstacle detection,” IEEE Trans. on Vehicular Technology, vol. 59, no. 3, pp. 1172–1182, March 2010.
R. Labayrade, D. Aubert, and J. P. Tarel, “Real time obstacle detection in stereovision on non flat road geometry through “V-disparity” representation,” Proc. IEEE Intelligent Vehicles Symposium, pp. 646–651, 2002.
K. Y. Lee, J. W. Lee, and N. Houshangi, “A stereo matching algorithm based on top-view transformation and dynamic programming for road-vehicle detection,” International Journal of Control, Automation, and Systems, vol. 7, no. 2, pp. 221–231, April 2009.
A. Cappalunga, S. Cattani, A. Broggi, M. S. McDaniel, and S. Dutta, “Real time 3D terrain elevation mapping using ants optimization algorithm and stereo vision,” Proc. IEEE Intelligent Vehicles Symposium, pp. 902–909, 2010.
A. Wedel, U. Franke, H. Badino, and D. Cremers, “B-spline modeling of road surfaces with an application to free space estimation,” IEEE Trans. on Intelligent Transportation Systems, vol. 10, no. 4, pp. 572–583, December 2009.
S. Kubota, T. Nakano, and Y. Okamoto, “A global optimization algorithm for real-time on-board stereo obstacle detection systems,” Proc. IEEE Intelligent Vehicles Symposium, pp. 7–12, 2007.
K. Y. Lee and J. W. Lee, “Stereo-vision based road slope estimation and free space detection on road,” Journal of Institute of Control, Robotics and Systems, vol. 17, no. 3, pp. 199–205, March 2011.
F. S. Hillier, Introduction to Operations Research, 8th edition, McGraw-Hill, 2006.
G. Y. Song and J. W. Lee, “Accurate dense stereo matching of slanted surfaces using 2D integral images,” Proc. International Conference on Computer Vision Systems, pp. 828–833, 2013.
R. Y. Tsai, “A versatile camera calibration technique for high accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses,” IEEE Journal of Robotics and Automation, vol. RA-3, no. 4, pp. 323–344, August 1987.
R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd edition, Prentice Hall, 2001.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Lee, KY., Park, JM. & Lee, JW. Estimation of longitudinal profile of road surface from stereo disparity using Dijkstra algorithm. Int. J. Control Autom. Syst. 12, 895–903 (2014). https://doi.org/10.1007/s12555-013-0478-x
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12555-013-0478-x