基于建筑物轮廓的地面激光点云与影像匹配点云配准研究

Research on registration of terrain laser scanning point cloud and image matching point cloud based on building footprint

为了高精度融合异源数据,进而充分表达建筑物的顶面及立面信息,提出基于建筑物轮廓特征的地面激光点云与影像匹配点云配准方法。通过边缘估计提取影像匹配点云建筑物屋顶轮廓,利用α-shape算法匹配提取地面激光点云建筑物屋檐轮廓,运用主成分分析算法、质心约束及罗德里格斯公式实现两种轮廓点云的粗配准,根据ICP算法完成精配准。实验结果表明该方法能够实现跨模态数据的优势互补,有效提高影像与点云配准的计算效率和配准精度。

In order to fuse heterogeneous data with high precision,then express the buildings roof and facade information fully,this paper proposed a registration method of terrain laser scanning point cloud and image matching point cloud based on buil-ding footprint features.It extracted image matching point cloud building roof edge by boundary estimation,got terrain laser scanning point cloud building eaves boundary byα-shape algorithm,completed two footprint point cloud’s coarse registration by principal component analysis algorithm,centroid constraint and Rodrigues’s formula,finished fine registration according to the ICP algorithm.Experimental results show that the method can combine the advantages of cross-modal data,and improve the calculation efficiency and registration accuracy of image and point cloud registration effectively.