This paper achieves out a new Delaunay triangulation algorithm. Firstly, the self-adaptation grid space division was proposed to realize the balanced logical grid division for massive point cloud data. Secondly, from far to near order the sequence of points in each grid by distance to the grid center and find out the nearest point and mark it as the central point. Thirdly, the TIN was built with by a new general-division Delaunay triangulation algorithm, which uses traditional insertion method to build TIN and add only one point from each grid at one times to form new TIN. When building TIN we use find-insertion method firstly and hereafter use topology-insertion method to keep high efficiency. This algorithm has good efficiency because it successfully avoided the merge process of sub grid triangulation mesh. Finally, the topological closure detection mechanism was established, and the independent parallel multithreading was started to model the rest points by topology-insertion algorithm limit to every grid space, which made the triangulation modeling of the whole space efficient. The method of this paper improved the support capacity of space modeling for massive point cloud data obviously.
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