Computer Graphics
TU Braunschweig

A Fast and Robust Approach to Lane Marking Detection and Lane Tracking


A Fast and Robust Approach to Lane Marking Detection and Lane Tracking

We present a lane detection algorithm that robustly detects

and tracks various lane markings in real-time. The first

part is a feature detection algorithm that transforms several input images into a top view perspective and analyzes local histograms. For this part we make use of state-of-the-art graphics hardware. The second part fits a very simple and flexible lane model to these lane marking features. The algorithm was thoroughly tested on an autonomous vehicle that was one of the finalists in the 2007DARPAUrban Challenge. In combination with other sensors, i.e. a lidar, radar and vision based obstacle detection and surface classification, the autonomous vehicle is able to drive in an urban

scenario at up to 15 mp/h.


Author(s):Christian Lipski, Björn Scholz, Kai Berger, Christian Linz, Timo Stich, Marcus Magnor
Published:July 2008
Type:Article in conference proceedings
Book:Proc. IEEE Southwest Symposium on Image Analysis and Interpretation (IEEE Computer Society)
Presented at:IEEE Southwest Symposium on Image Analysis and Interpretation
Project(s): Computer Vision Algorithms for the DARPA Urban Challenge 2007 

BibTex PDF 



@inproceedings{lipski2008ssiai,
  title = {A Fast and Robust Approach to Lane Marking Detection and Lane Tracking},
  author = {Lipski, Christian and Scholz, Bj{\"o}rn and Berger, Kai and Linz, Christian and Stich, Timo and Magnor, Marcus},
  booktitle = {Proc. {IEEE} Southwest Symposium on Image Analysis and Interpretation},
  organization = {{IEEE} Computer Society},
  volume = {2008},
  pages = {57--60},
  month = {Jul},
  year = {2008}
}

Authors