摘要
针对无人机倾斜摄影测量与地面移动设备采集的点云存在空间基准不统一的问题,本文提出了一种基于平面几何一致性的全局点云配准算法。该算法通过自适应体素提取城市建筑立面、地面等场景中的多尺度平面,基于局部平面构建几何约束,将基于点的配准简化为基于平面聚类的配准,显著降低计算复杂度。试验结果表明,该算法在跨平台、多期点云配准中达到厘米级精度,为城市三维建模与数字孪生应用等提供了高效的多源数据融合方案,具有工程实用价值。
To address the spatial reference inconsistency between point cloud acquired by airborne oblique photogrammetry and ground mobile laser scanning,this paper proposes a global registration algorithm based on planar geometric consistency.The algorithm employs adaptive voxel-based segmentation to extract multi-scale planar primitives(e.g.,building facades,road surfaces)from urban scenes and constructs geometric constraints using local planar clusters as optimization elements.Experimental results demonstrate that the proposed method achieves centimeter-level accuracy in cross-platform and multi-temporal point cloud registration.This algorithm provides an efficient solution for multi-source data fusion in urban 3D modeling and digital twin applications,offering practical value for geospatial engineering.
作者
陈嘉豪
CHEN Jiahao(Shanghai Surveying and Mapping Institute,Shanghai 200063,China;Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities,MNR,Shanghai 200063,China)
出处
《测绘通报》
北大核心
2025年第S1期115-118,共4页
Bulletin of Surveying and Mapping
关键词
点云配准
平面几何约束
体素
倾斜摄影
point cloud registration
planar geometric constraints
voxel-based segmentation
oblique photogrammetry
