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Camera-based lane border detection in arbitrarily structured environments

机译:在任意结构化环境中基于摄像机的车道边界检测

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In this paper we present a new approach for monocular image based lane border detection in situations where the characteristics of the pavement and the lane border are unknown. To achieve real time performance on standard hardware we analyze statistical characteristics of 1D signals on certain profile lines to find different types of features which belong to the lane border. These features are used for fitting a border model in. The proposed method shows good results in complex situations. It was evaluated in different scenarios with cobblestone pavement, lowered curbs, lane markers, parking cars defining the lane border as well as disturbances on the road like shadows, dirt and asphalt damages. The method was successfully used within the Volkswagen research vehicle ‘eT’ (electronic Transporter).
机译:在本文中,我们提出了一种在路面和车道边界特征未知的情况下基于单眼图像的车道边界检测的新方法。为了在标准硬件上实现实时性能,我们分析了某​​些轮廓线上的一维信号的统计特征,以发现属于车道边界的不同类型的特征。这些特征用于拟合边界模型。所提出的方法在复杂情况下显示出良好的效果。在不同的场景中对它进行了评估,包括鹅卵石路面,降低的路缘石,车道标记,定义车道边界的停车车以及道路上的干扰(例如阴影,灰尘和沥青损坏)。该方法已在大众汽车的研究工具“ eT”(电子运输车)中成功使用。

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