摘要
Abstract
To improve the construction effect of urban reality models and provide data support for smart city construction,a three-dimensional(3D)reconstruction method of urban reality based on oblique photography and laser point cloud fusion was proposed.After converting laser point cloud data from different stations and point cloud data extracted from oblique images to the target coordinate system,preliminary matching of multi-source point clouds was completed.Then,an improved iterative nearest point algorithm with rotation angle constraints and dynamic iteration coefficients was used for accurate registration,thus completing multi-source point cloud fusion.In the Context Capture software,the fused point cloud data was processed to generate a triangular mesh representation of the 3D surface.After optimizing and adjusting the triangular mesh,a triangular mesh model was obtained,and texture maps were added to the model,successfully achieving 3D reconstruction of urban reality.The experimental results show that the reconstructed 3D model of urban reality exhibits outstanding texture details and realistic shapes,with extremely small point position errors between the original point cloud data and the reconstructed model ranging from 0.005-0.017 m.关键词
倾斜摄影/激光点云/三维重建/迭代最近点算法/三角网格模型/旋转角约束Key words
oblique photography/laser point cloud/three-dimensional(3D)reconstruction/iterative nearest point algorithm/triangular mesh model/rotation angle constraint分类
测绘与仪器
