A novel skyline context descriptor for rapid localization of terrestrial laser scans to airborne laser scanning point clouds
A novel skyline context descriptor for rapid localization of terrestrial laser scans to airborne laser scanning point clouds
复制标题
一种新颖的天际线上下文描述符，用于将地面激光扫描快速定位到机载激光扫描点云
DOI：
10.1016/j.isprsjprs.2020.04.018
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发表时间：
2020
影响因子：
12.7
通讯作者：
Pan Yue
中科院分区：
文献类型：
--
作者：
Liang Fuxun;Yang Bisheng;Dong Zhen;Huang Ronggang;Zang Yufu;Pan Yue
利用机载激光扫描（ALS）和地面激光扫描（TLS），可以快速获取地表的俯视和侧视信息。然而，由于不同的透视图、分辨率和范围，将多个TLS扫描自动定位到ALS具有挑战性。为了解决这个问题，本文提出了一种新的天际线上下文为基础的方法。首先，提取ALS中的地面点并将其用作潜在的TLS位置，并生成相应的天际线上下文。在此基础上，建立了一个基于三维skyline的k-d树，用于搜索TLS扫描的相应粗定位。最后的细化是由修剪迭代最近点算法（T-ICP）。5个不同ALS大小的数据集和超过一百个TLS扫描进行评估所提出的方法的性能。对于一个平均点距为0.1 m的ALS数据，平均定位精度达到约0.13 m。实验结果表明，该方法能有效地将TLS扫描图像自动定位到ALS点云上，具有精度高、适应性强等优点。
By utilizing the airborne laser scanning (ALS) and terrestrial laser scanning (TLS), the land surface information from both top view and side view can be captured rapidly. However, due to the different perspective views, resolutions, and ranges, the automatic localization of multiple TLS scans to ALS is challenging. To address this issue, this paper proposes a novel skyline context-based method. First, the ground points in ALS are extracted and used as potential TLS locations, and the corresponding skyline contexts are generated. After that, a 3D skyline-based k-d tree is built for searching the corresponding coarse localizations of TLS scans. The final refinement is done by the trimmed iterative closest point algorithm (T-ICP). 5 datasets with different ALS sizes and over one hundred TLS scans are undertaken to evaluate the performance of the proposed method. For one ALS data with mean point distance of 0.1 m, the average localization accuracy reached about 0.13 m. The experimental results indicate that the proposed method performs well for automatic localization of TLS scans to ALS point clouds, with advantages in both precision and adaptability.