散乱三维测量数据构建三角形网格模型的研究

Research on Reconstruction of Triangular Mesh Model from Scattered 3D Measured Data

三角网格模型广泛应用于曲面重构、快速原型制造和三维真实感显示等领域。针对三维测量得到的无拓扑关系的散乱无序点集,提出了一种三角网格模型构建算法。首先进行点云粗分组,然后从最高点根据Delaunay划分原则,按照循环扩展的思路生成三角形网格。通过控制合适的三角形生长条件,有效避免了三角面片交叉错乱、退化、法向量不一致缺陷。应用实例表明,该算法能有效完成各类复杂型面三维测量数据的三角网格模型构建。

Triangular mesh model is widely used in surface reconstruction, rapid prototype manufacture and real display. For the scattered points set without any topological relation, this paper presents an algorithm for triangular mesh model reconstruction. First the point cloud is roughly divided into groups, then triangular mesh is developed in circulation from the toppest point base on the principle of Delaunay triangulation. By controlling appropriate triangle growing conditions, the errors llke triangle intercrossing, degeneration, inconsistent normal and so on are effectively avoided. Application examples prove that the algorithm can effectively accomplish all kinds of triangular mesh model reconstructions from point cloud in complex surface.