Model-based curved lane detection using geometric relation between camera and road plane

被引：0
作者：
School of Computer Science and Engineering, Kyungpook National University, Korea, Republic of [1 ]
机构：
[1] School of Computer Science and Engineering, Kyungpook National University
来源：
J. Inst. Control Rob. Syst. | / 2卷 / 130-136期
关键词：
Curved lane detection; Feature extraction; Lane detection;
D O I：
10.5302/J.ICROS.2015.14.9008
中图分类号：
学科分类号：
摘要：
In this paper, we propose a robust curved lane marking detection method. Several lane detection methods have been proposed, however most of them have considered only straight lanes. Compared to the number of straight lane detection researches, less number of curved-lane detection researches has been investigated. This paper proposes a new curved lane detection and tracking method which is robust to various illumination conditions. First, the proposed methods detect straight lanes using a robust road feature image. Using the geometric relation between a vehicle camera and the road plane, several circle models are generated, which are later projected as curved lane models on the camera images. On the top of the detected straight lanes, the curved lane models are superimposed to match with the road feature image. Then, each curve model is voted based on the distribution of road features. Finally, the curve model with highest votes is selected as the true curve model. The performance and efficiency of the proposed algorithm are shown in experimental results. © ICROS 2015.
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页码：130 / 136
页数：6
相关论文
共 14 条
  • [1] Want J.S., Knipling R.R., Single-vehicle roadway departure crashes: problem size assessment and statistical description, (1994)
  • [2] Dagan E., Mano O., Stein G.P., Shashua A., Forward collision warning with a single camera, IEEE Intelligent Vehicles Symposium, pp. 37-42, (2004)
  • [3] Chen M., Jochem T., Pomerleau D., AURORA: a visionbased roadway departure warning system, IEEE Conference on Intelligent Robots and Systems, pp. 1-4, (1995)
  • [4] Liu W., Zhang H., Duan B., Yuan H., Zhao H., Visionbased real-time lane marking detection and tracking, 11th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 49-54, (2008)
  • [5] Wang Y., Teoh E.K., Shen D., Lane detection and tracking using B-Snake, Image and Vision Computing, 22, 4, pp. 269-280, (2004)
  • [6] Chiu K.Y., Lin S.F., Lane detection using color-based segmentation, IEEE Conference on In Intelligent Vehicles Symposium, pp. 706-711, (2005)
  • [7] Deng J., Han Y., A real-time system of lane detection and tracking based on optimized RANSAC B-spline fitting, Proc. of the 2013 Research in Adaptive and Convergent Systems, pp. 157-164, (2013)
  • [8] Aly M., Real time detection of lane markers in urban streets, IEEE Intelligent Vehicles Symposium, pp. 7-12, (2008)
  • [9] Revilloud M., Gruyer D., Pollard E., An improved approach for robust road marking detection and tracking applied to multi-lane estimation, IEEE Intelligent Vehicles Symposium, pp. 783-790, (2013)
  • [10] (2010)
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