Sensors | |
Robust Lane Sensing and Departure Warning under Shadows and Occlusions | |
Rodolfo Tapia-Espinoza1  | |
[1] Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860, Casilla 306-22, Santiago, Chile; E-Mail | |
关键词: road sensing; lane detection and tracking; lane departure warning; mean-shift clustering; gabor filters; Gaussian Markov Random Fields; RANSAC; | |
DOI : 10.3390/s130303270 | |
来源: mdpi | |
【 摘 要 】
A prerequisite for any system that enhances drivers' awareness of road conditions and threatening situations is the correct sensing of the road geometry and the vehicle's relative pose with respect to the lane despite shadows and occlusions. In this paper we propose an approach for lane segmentation and tracking that is robust to varying shadows and occlusions. The approach involves color-based clustering, the use of MSAC for outlier removal and curvature estimation, and also the tracking of lane boundaries. Lane boundaries are modeled as planar curves residing in 3D-space using an inverse perspective mapping, instead of the traditional tracking of lanes in the image space,
【 授权许可】
CC BY
© 2013 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190037692ZK.pdf | 4726KB | download |