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针对传统的建筑物重建方法中,由机载LiDAR点云建立的模型表达复杂的问题,提出了一种基于多边形分解的建筑物重建方法。采用基于欧氏距离的聚类算法和随机抽样一致性算法,提取建筑物的不同平面,简化复杂结构的建筑物;基于检测出来的平面,对其进行分解,以最小外接矩形和内部空洞的布尔运算结果来表示,并进行建模。实验结果表明,该文方法可以有效简化建模过程,依据屋顶面之间边缘与空洞的关系优化结果也使得边缘更加准确,同时也更适合于CSG模型的表示。
In the traditional method of building reconstruction, the model built by airborne LiDAR point cloud expresses complex problems, and a reconstruction method based on polygon decomposition is proposed. Euclidean distance-based clustering algorithm and random sampling consistency algorithm are used to extract different planes of buildings and simplify buildings with complicated structures. Based on the detected planes, the decomposition is carried out. The minimum enclosing rectangles and internal holes in Boolean The result of the operation is expressed and modeled. The experimental results show that the proposed method can effectively simplify the modeling process and optimize the results based on the relationship between the edge and the cavity in the roof surface to make the edge more accurate and more suitable for the representation of the CSG model.