散乱点云数据空间三角网构建方法的研究

摘要

Point cloud data three -dimensional modeling is mainly focusing on the surface of the target object modeling grid .Triangle as the basic element of 3 dimension modeling , it is not only simple , but also can express geometrical surface complex properties effec-tively.Delaunay triangulation is currently the most widely used triangle subdivision method ;it can maximally avoid the production of long and narrow triangle , it and can keep the uniqueness of network type no matter where to start creating network .On the basis of the existing grow algorithm study , this article proposed a new algorithm:That is on the basic of the 2 dimension grow algorithm , it uses the normal vector of space to seek the third point of the triangle and to create space triangulation .The advantage of this algorithm is:it is not only suitable for a massive number of point cloud data to construct the space triangulation , but also reflect the object's surface characteristics of build space triangulation well .%点云数据三维建模主要是对目标物体的表面进行网格建模。三角形作为三维建模的基本表示元素，不仅性质简单，而且可以有效地表示物体表面复杂的几何属性。 Delaunay三角网是当前使用最广泛的三角剖分方法，它能够最大限度地避免狭长三角形的产生，并且无论从何处开始建网都能保持网型的唯一性。本文在已有生长算法研究的基础上提出了一个新的算法：即在二维生长算法的基础上，利用空间三角形的法向量来进行第三点的搜索构建空间三角网。该算法的优点是：适合大量点云数据构建空间三角网、构建的空间三角网可以很好地反映出物体的表面特征。