Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds
Semiautomated Extraction of Street Light Poles From Mobile LiDAR Point-Clouds
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DOI：
10.1109/tgrs.2014.2338915
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发表时间：
2015-03
影响因子：
8.2
通讯作者：
Yongtao Yu;Jonathan Li;H. Guan;Cheng Wang;Jun Yu
中科院分区：
文献类型：
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作者：
Yongtao Yu;Jonathan Li;H. Guan;Cheng Wang;Jun Yu
提出了一种从车载移动的激光雷达（LiDAR）点云数据中提取路灯灯杆的新算法。首先，该算法快速检测路缘线和分段的点云到道路和非路面点的基础上的轨迹数据记录的综合定位和定向系统车载车辆。其次，该算法使用新颖的成对3D形状上下文从分割的非道路表面点中准确地提取路灯杆。所提出的算法进行了测试上的一组点云采集RIEGL VMX-450移动的激光雷达系统。结果表明，路面分割正确，路灯杆提取稳健，完整性超过99%，正确性超过97%，质量超过96%，证明了该算法从大量移动的LiDAR点云中分割路面和提取路灯杆的有效性和可行性。
This paper proposes a novel algorithm for extracting street light poles from vehicleborne mobile light detection and ranging (LiDAR) point-clouds. First, the algorithm rapidly detects curb-lines and segments a point-cloud into road and nonroad surface points based on trajectory data recorded by the integrated position and orientation system onboard the vehicle. Second, the algorithm accurately extracts street light poles from the segmented nonroad surface points using a novel pairwise 3-D shape context. The proposed algorithm is tested on a set of point-clouds acquired by a RIEGL VMX-450 mobile LiDAR system. The results show that road surfaces are correctly segmented, and street light poles are robustly extracted with a completeness exceeding 99%, a correctness exceeding 97%, and a quality exceeding 96%, thereby demonstrating the efficiency and feasibility of the proposed algorithm to segment road surfaces and extract street light poles from huge volumes of mobile LiDAR point-clouds.