基于地面激光扫描数据, 提出了一种新的建筑物边界规则化方法, 不仅可以对建筑物整体而且可以对不同侧面进行规则化, 包括立面墙面、门和窗户等.首先对海量原始激光点云利用高效的随机采样一致性算法分割为不同的平面面片, 然后利用2D α-shapes算法提取建筑物点云数据.在此基础上, 利用本文提出的边界规则化算法产生一个规则多边形进而实现建筑物边界规则化.利用实际地面扫描数据对该算法进行验证, 表明本文方法可以针对不同密度的点云进行自适应调整, 不仅效率高, 而且可以达到非常满意的建筑边界规则化效果.该研究成果对于利用地面激光扫描数据进行建筑物三维建模具有一定的参考意义.

Traditional methods for boundary regularization mainly take airborne laser scanning (ALS) data as input and process the point clouds of building roofs with simple planar shapes, while terrestrial laser scanning (TLS) could acquire more complete and denser point clouds of building facades with more complex shapes. In this paper a new boundary regularization approach based on TLS data is proposed. It can deal with several types of point clouds for buildings facades, including walls, doors and windows. Firstly, raw point clouds are segmented into planar facades by using an efficient RANSAC algorithm. Secondly, the boundary points are extracted by using a 2D α-shapes algorithm. Based on the boundary points, a fitting regular polygon is generated by using the boundary regularization approach proposed in the paper. The experimental results show that the proposed approach is self-adaptive to point clouds with different density. Meanwhile, it is demonstrated that the approach is effective and efficient, and could provide reliable and satisfactory regularization results.