针对颅面点云数据的Deluney三角网构建方法

Deluney triangulation of craniofacial point cloud

针对颅骨和面皮点云数据,提出一种新的Deluney-三角网构建算法。该算法将点云数据分为两层,将上下两层轮廓线点列合理连接以生成三角面片集合,给出了面片个数及跨距应满足的合理条件;在三角网格构建时,考虑到颅面点云数据对应的不同曲率及孔洞等情形,分为四类(通常情况、孔洞、椎体链接、缝合),分别进行处理,利用最小对角线方法进行三角化,实验表明该算法保持了比较精确的轮廓。

This article gives a new method for the Deluney Triangulation of craniofacial point cloud.By dividing the point cloud into two layers,the points are connected from the upper and lower to generate a set of triangular patches;during the triangulation process,taking into account the certain holes and the difference of curvature of the facial point cloud data,the steps are classfied into four groups（usually,hole,vertebral links,sewing）to process the points separately,by taking the advantage of the smallest diagonal method.Experimental results show that the algorithm maintains a relatively accurate profile of the face and skull.