Due to the limited sensing ability with the single-view camera and the real-time requirement for multi-view scenarios or deep learning-based methods in complex scenes, the output of lane detection is not applicable for the actual lane departure warning system. To tackle this challenge, the authors propose a fast and robust approach for lane detection based on well-designed multi-camera fusion, integrating vanishing point estimation, and specified feature fitting strategies. To meet real-time demand, several simple but effective image processing means are introduced and improved. Concretely, on account of statistical information, the authors’ method carries out an improved region of interest selection to speed up the detection. Afterwards, they used the B-spline fitting lane line on the strength of the RANdom SAmple consensus algorithm for the front view image detection and improved the Hough algorithm for the two rear-view images correspondingly. Using coordinate conversion and self-designed fusion strategy, they get the robust lane information based on symmetrical lane detection from the left/right sides of both front and side views. Experimental results in newly introduced multi-camera scenarios show that their multi-camera fusion framework contributes to significant improvement in accuracy and robustness in comparison with traditional methods.
Fast and robust approaches for lane detection using multi-camera fusion in complex scenes
IET Intelligent Transport Systems ; 14 , 12 ; 1582-1593
2020-09-02
12 pages
Article (Journal)
Electronic Resource
English
feature fitting strategies , real-time requirement , symmetrical lane detection , sensor fusion , statistical information , learning (artificial intelligence) , rear-view images , random sample consensus algorithm , Hough algorithm , robust lane information , feature extraction , splines (mathematics) , Hough transforms , deep learning-based methods , coordinate conversion , edge detection , complex scenes , multiview scenarios , B-spline fitting lane line , multicamera fusion framework , self-designed fusion strategy , image sensors , actual lane departure warning system , single-view camera , cameras , front view image detection , image processing
Metadata by IET is licensed under CC BY 3.0
Lane Detection System for Night Scenes
SAE Technical Papers | 2018
|Lane Detection System for Night Scenes
British Library Conference Proceedings | 2018
|Pedestrian lane detection in unstructured scenes for assistive navigation
British Library Online Contents | 2016
|Vision-Based Lane Detection Algorithm in Urban Traffic Scenes
Tema Archive | 2014
|