A line-based approach for precise extraction of road and curb region from mobile mapping data
A line-based approach for precise extraction of road and curb region from mobile mapping data
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DOI：
10.5194/isprsannals-ii-5-243-2014
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发表时间：
2014-05
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影响因子：
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通讯作者：
R. Miyazaki;M. Yamamoto;E. Hanamoto;H. Izumi;K. Harada
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作者：
R. Miyazaki;M. Yamamoto;E. Hanamoto;H. Izumi;K. Harada
点云中的平面结构检测是道路、路缘等基础设施维护等应用中的重要环节，因为大多数人工结构都是由平面组成的。移动地图系统可以在标准速度下获取大量的点数。然而，在配备高端激光扫描系统的情况下，点的分布密度不均匀。在基于点的方法中，这种情况给利用邻接点计算几何信息的方法带来了问题。为了从点密度不均匀的点云中检测出边界精确的平面结构，本文提出了一种基于线的区域生长方法。通过从输入云适当地创建线段来维护平面结构的精确边界。改进了邻域的定义和法矢的估计，使之适用于基于直线的区域生长。通过与人工提取的路缘点进行比较，结果表明，检测出的路缘点达到98%以上。并且，大约90%的道路和路缘之间的边界点的检测距离误差小于0.005米。
Planar structure detection from point clouds is important process in many applications such as maintenance of infrastructure facility including roads and curbs because most artificial structures consists of planar surfaces. The Mobile Mapping System can obtain a large amount of points with traveling at a standard speed. However, in the case that the high-end laser scanning system is equipped, the distribution density of points is uneven. In the point-based method, this situation causes the problem to the method of calculating geometric information using neighborhood points. In this paper, we propose a line-based region growing method in order to detect planar structures with precise boundary from point clouds with uneven distribution density of points. The precise boundary of a planar structure is maintained by appropriately creating line segments from the input clouds. We adapt the definition of neighborhood and the estimation of the normal vector to the line-based region growing. The evaluation by comparing our result with manually extracted points shows that more than 98% of curb points are detected. And, about 90% of the boundary points between a road and a curb are detected with less than 0.005 meters of the distance error.