Road lane modeling based on RANSAC algorithm and hyperbolic model

This paper presents a simple and fast road lane detection and modeling method with high robustness. We use IPM transformation to get a "bird's eye view" of the road and do some image processing to avoid noise, then divide regions for each lane and implement a improved RANSAC algorithm...

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Bibliographic Details
Published in2016 3rd International Conference on Systems and Informatics (ICSAI) pp. 97 - 101
Main Authors Shikun Xu, Ping Ye, Shengsheng Han, Hanxu Sun, Qingxuan Jia
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2016
Subjects
ADAS
Cameras
Computational modeling
Filtering
Hyperbolic Model
IPM
Lane Modeling
Mathematical model
RANSAC
Roads
Transforms
Vehicles
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Summary:This paper presents a simple and fast road lane detection and modeling method with high robustness. We use IPM transformation to get a "bird's eye view" of the road and do some image processing to avoid noise, then divide regions for each lane and implement a improved RANSAC algorithm to fit Hyperbolic model defined by us. Our method can successfully detect road lanes in various conditions and achieve reasonable results on KITTI dataset.
DOI:10.1109/ICSAI.2016.7810937