基于车载LiDAR数据的建筑物三维重建

车载LiDAR点云数据量大且杂乱无章,当前尚没有完整算法来实现建筑物点云的自动分割和模型重建,特别是带有纹理信息的模型重建.以一栋结构复杂的建筑物为例,结合建筑物实际特征,采用自动与手动相结合、先简单后复杂、凹凸一致性等原则对数据进行分割和滤波处理;再采用点云数据与CAD底图配准的方式进行三维重建、纹理映射和渲染,从而实现结构复杂建筑物的真实三维重建.

3D buildings reconstruction based on vehicle-borne laser-scanning data

The amount of vehicle-borne LiDAR point cloud data is tremendously and desultorily. Currently, there is still no one who complete and rigorous algorithm for point cloud auto-segmentation and model recon- struction of buildings, especially with the texture information of model reconstruction. In this paper, the author takes the building with a complex structure as an example. Firstly, considering the actual characteristics of the buildings, we take the automatic and manual methods to treat the process of segmentation and filtering by the principle of the consistency of concave and convex from simple to difficult. Secondly, we utilize the way of combining the point cloud data and CAD base map to make the quasi-three-dimensional reconstruction. Finally, the texture of models should be mapped and rendered. After all these work done, real three-dimensional model construction can be developed. The method has practical value to processing and modeling vehicle laser scan data.