Line segment extraction for large scale unorganized point clouds
Line segment extraction for large scale unorganized point clouds
复制标题
大规模无组织点云的线段提取
DOI：
10.1016/j.isprsjprs.2014.12.027
复制
发表时间：
2015-04-01
影响因子：
12.7
通讯作者：
Li, Jonathan
中科院分区：
文献类型：
--
作者：
Lin, Yangbin;Wang, Cheng;Li, Jonathan
图像中的线段检测已经是一个被广泛研究的课题，尽管它在三维点云中受到的关注还很少。得益于当前的激光雷达设备，大规模点云正变得越来越普遍。大多数人造物体的表面都是平的。出现在两对平面相交处的线段提供了有关点云几何内容的重要信息，这对于自动重建和分割建筑物特别有用。提出了一种能够从大规模原始扫描点精确提取平面相贯线段的新方法。同时提取3D线支撑区域，即直线结构附近的点集。3D线支撑区域由我们的线段半平面(LSHP)结构来拟合，该结构为线段提供了几何约束，使得线段更加可靠和准确。我们在LiDAR设备获取的大规模、复杂的真实场景的点云上演示了我们的方法。我们还展示了三维线支撑区域及其LSHP结构在城市场景提取中的应用。(C)2015年国际摄影测量和遥感学会(摄影测量和遥感学会)。爱思唯尔出版，版权所有。
Line segment detection in images is already a well-investigated topic, although it has received considerably less attention in 3D point clouds. Benefiting from current LiDAR devices, large-scale point clouds are becoming increasingly common. Most human-made objects have flat surfaces. Line segments that occur where pairs of planes intersect give important information regarding the geometric content of point clouds, which is especially useful for automatic building reconstruction and segmentation. This paper proposes a novel method that is capable of accurately extracting plane intersection line segments from large-scale raw scan points. The 3D line-support region, namely, a point set near a straight linear structure, is extracted simultaneously. The 3D line-support region is fitted by our Line-Segment-Half-Planes (LSHP) structure, which provides a geometric constraint for a line segment, making the line segment more reliable and accurate. We demonstrate our method on the point clouds of large-scale, complex, real-world scenes acquired by LiDAR devices. We also demonstrate the application of 3D line-support regions and their LSHP structures on urban scene abstraction. (C) 2015 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.