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Using mobile LiDAR point clouds for traffic sign detection and sign visibility estimation

机译:使用移动LiDAR点云进行交通标志检测和标志可见性估计

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This paper presents a novel method for traffic sign detection and visibility evaluation from mobile Light Detection and Ranging (LiDAR) point clouds and the corresponding images. Our algorithm involves two steps. Firstly, a detection algorithm based on high retro-reflectivity of the traffic sign from the MLS point clouds is designed for sign detection in complicated road scenes. To solve the spatial features of traffic signs, we also create geo-referenced relations between traffic signs and roads according to the normal of ground. Secondly, we propose a visibility estimation method to evaluate the visibility level of the traffic sign based on a combination of visual appearance and spatial-related features. The proposed algorithm is validated on a set of transportation-related point-clouds acquired by a RIEGL VMX-450 LiDAR system. The experiment results demonstrate that the efficiency and reliability of the proposed algorithm in detection traffic signs are robust, and also prove the potential of using mobile LiDAR data for traffic sign visibility evaluation.
机译:本文提出了一种新的流量标志检测和来自移动光检测和范围(LIDAR)点云和相应图像的可见性评估方法。我们的算法涉及两个步骤。首先,基于来自MLS点云的交通标志的高复古反射率的检测算法被设计用于复杂的道路场景中的标志检测。为了解决交通标志的空间特征,我们还根据地面的正常创建交通标志和道路之间的地理引用关系。其次,我们提出了一种可见性估计方法,以评估基于视觉外观和空间相关的特征的组合来评估交通标志的可见度水平。所提出的算法在由RieGL VMX-450 LIDAR系统获取的一组运输相关的点云上验证。实验结果表明,检测交通标志中所提出的算法的效率和可靠性是强大的,并且还证明了使用移动激光器数据进行交通标志可见性评估的可能性。

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