【摘要】 为解决细分过程中曲面网格增长速度过快的问题,以二面角准则为自适应细分准则,提出一种基于顶点平坦度的Catmull-Clark自适应细分算法。该算法通过计算顶点1-邻域内所有面之间的法向夹角,定义顶点平坦度作为阈值来判断网格面是否需要进一步细分。以发动机零件为例,应用Catmull-Clark基本算法和自适应算法对网格曲面细分展开对比分析。实验结果显示,通过调节细分阈值的大小,自适应算法能减少细分过程中产生的网格数量,有效降低网格增长速度,减少内存占有空间和网格细分时间,细分算法效率得到明显提高。更多还原

【Abstract】 In order to solve the problem that the surface mesh grows too fast during the subdivision process,a Catmull-Clark adaptive subdivision algorithm based on vertex flatness was proposed by using the dihedral angle criterion as the adaptive subdivision criterion.The algorithm first calculated the normal angle between all surfaces in the vertex 1-neighborhood,then calculated the average value of all angles,and finally defined the flatness of vertices as the threshold to determine whether the mesh surface needs further subdivision.Taking theengine parts as an example,the surface was subdivided using the Catmull-Clark adaptive algorithm and the original Catmull-Clark algorithm.The experimental results showed that the adaptive algorithm can reduce the number of meshes generated in the subdivision process by adjusting the size of subdivision threshold,effectively reduce the growth rate of meshes,reduce memory space and subdivision time,and improve the efficiency of subdivision algorithm significantly.更多还原