Multi-frames based real-time road detection method for autonomous vehicle

Usually we evaluate a certain road detection method from two aspects, the detecting performance and the executing time. Normally there is a compromise between these two criteria. This paper is focused on how to provide a reliable and real-time road detection result for an autonomous vehicle. By using a vanishing point based high reliability detection method for the leading frame and Hough transformation based real-time method for the following frames, we solve the contradiction of the detecting performance and the executing time. In the vanishing point detection, we use Gabor filters to get the texture information of the road and use particle swarm optimization to increase the efficiency.

[1]  Antonio M. López,et al.  Road Detection Based on Illuminant Invariance , 2011, IEEE Transactions on Intelligent Transportation Systems.

[2]  Anil K. Jain,et al.  Lane boundary detection using a multiresolution Hough transform , 1997, Proceedings of International Conference on Image Processing.

[3]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[4]  Christopher Rasmussen Texture-Based Vanishing Point Voting for Road Shape Estimation , 2004, BMVC.

[5]  Christopher Rasmussen,et al.  Grouping dominant orientations for ill-structured road following , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[6]  Camillo J. Taylor,et al.  Stochastic road shape estimation , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[7]  Mohamed Aly,et al.  Real time detection of lane markers in urban streets , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[8]  Hui Kong,et al.  Generalizing Laplacian of Gaussian Filters for Vanishing-Point Detection , 2013, IEEE Transactions on Intelligent Transportation Systems.

[9]  Alberto Broggi Robust real-time lane and road detection in critical shadow conditions , 1995, Proceedings of International Symposium on Computer Vision - ISCV.

[10]  Jean Ponce,et al.  General Road Detection From a Single Image , 2010, IEEE Transactions on Image Processing.