针对三维点云在泊松曲面重构过程中由于法线方向不一致而导致重构结果出现偏差的问题,提出一种基于改进法线方向的泊松曲面重构算法。利用包围盒将原始点云分割为若干个立方体体素,并将每个有效体素标记为“位置已知”或 “位置未知”。采用KD(k-dimensional)树对每个有效体素内的点云重新排序,利用主成分分析法进行法线估计,将新的顺序作为法线传播方向,实现点云法线的局部定向。针对 “位置已知”的体素,依据体素质心位置完成法线的全局定向;对于 “位置未知”的体素,则依据相邻体素的法线实现法线的全局定向。最后,结合法线定向结果对点云进行泊松曲面重构。实验结果表明,该算法能将复杂曲面点云的法线定向至同一侧,法线估计误差接近于0,能较好地实现泊松曲面重构,提高重构曲面的准确度。

This study proposes a Poisson surface reconstruction algorithm based on the improved normal orientation to verify the inaccurate reconstruction results obtained because of the inconsistent normal orientation of the three-dimensional point cloud in the Poisson surface reconstruction process. First, the original point cloud is segmented into a number of cubic voxels using the bounding box and each valid voxel is marked as “position known” or “position unknown”. Then, a k-dimensional tree is used to reorder the point cloud in each valid voxel; the principal component analysis method is used for normal estimation. The new order is used as the normal orientation of propagation to realize the local orientation of the point cloud normal. For voxels marked as “position known”, the global orientation of the normal is completed according to the physical position of the voxel centroid. For voxels marked as “position unknown”, the global orientation of the normal is implemented according to the normal of the adjacent voxels. Finally, Poisson surface reconstruction is performed on the point cloud in combination with the normal orientation results. Experimental results demonstrate that the proposed algorithm can orient the normal of the complex surface point cloud to the same side and that the deviation of the normal estimation is approximately 0. Thus, the proposed algorithm can properly realize Poisson surface reconstruction and improve the accuracy of reconstructed surface.