针对现有的曲面重建算法难以兼顾大规模采样数据的重建效率与重建曲面拓扑正确性的问题,提出一种基于局部Delaunay网格剖分的曲面增量重建算法.该算法采用波前扩展的策略,通过波前环的扩张、分裂、重叠面片的消除等步骤,将局部重建过程传播至每个样点的邻近区域,获得插值于采样点集的二维定向流形网格曲面,实现整个采样点集的增量拓扑重建;在曲面局部重建过程中,分别基于局部区域的Cocone算法与二维投影点集的De-launay网格剖分方法重建曲面的尖锐区域与平坦区域,其中局部区域重建曲面网格的边界的正确性由区域之外的少量辅助样点保护.实验结果表明,文中算法具有较高的重建效率,适用于封闭和非封闭海量点云数据的重建;且在采样密度符合要求的情况下,重建的网格曲面与原表面拓扑同构.%The current surface reconstruction algorithms are difficult to achieve a trade-off between effi-ciency and topological correctness of reconstruction for large point sets. For solving this problem, we pre-sent an incremental topological surface reconstruction algorithm based on local Delaunay triangulation. Taking the strategy of advancing fronts method, the local reconstruction process spread to the adjacent area of each point, so the whole sampling point set can be incrementally reconstructed. By updating the front wave in the way of expanding and splitting and eliminating duplicate facets in the meantime, the oriented 2-Manifolds mesh interpolated on sampling point set can be output. In the process of local reconstruction, the feature areas are reconstructed by Localized Cocone algorithm and the flat regions are reconstructed by 2D Delaunay triangulation of projection points. In order to ensure the correctness of local mesh, auxiliary points are added to the local regions. The experiment results show that this algorithm has high efficiency which makes it suitable for reconstructing closed and non-closed massive point cloud. When sampling den-sity condition requirement is met, its final reconstructed triangular mesh is topologically equivalent to the original surface.
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