基于点云数据的牙齿表面重建算法
Dental surface reconstruction algorithm based on point cloud data
作者：曹巍(四川大学计算机学院视觉合成图形图像国防重点学科实验室)；袁赞(四川大学计算机学院视觉合成图形图像国防重点学科实验室)；吴志红(四川大学计算机学院视觉合成图形图像国防重点学科实验室)
Author：CAO Wei(National Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University)；YUAN Zan(National Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University)；WU Zh- Hong(National Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University)
收稿日期：2014-08-05 年卷（期）页码：2015,52(3):517-522
期刊名称：四川大学学报: 自然科学版
Journal Name：Journal of Sichuan University (Natural Science Edition)
关键字：点云模型; K邻域搜索; 最小二乘; 区域增长; 三维表面重建
Key words：Point Cloud Model; KNN Search; Least Squares; Region Growing; 3D Surface Reconstruction
基金项目：国家高技术研究发展计划（2012AA011804）
中文摘要
由三维扫描仪对牙齿进行扫描, 得到散乱的点云模型, 首先通过构建K D树的方法对每个点进行K邻域搜索; 然后根据这种邻域关系, 利用最小二乘原理拟合平面, 估算出每个点的法向量信息; 接着确定点云边界, 选取极值点作为初始点并建立种子三角形; 最后采用基于多约束的局部最优三角网格生长算法, 从种子三角形开始, 以边为扩展条件, 逐层搜索点并建立新的三角形; 在此过程中添加了四个约束条件, 能够较好的选取扩展点并对已存在的三角形边向外扩展, 从而形成互相邻接的三角形网格, 实现了牙齿表面的重建.
英文摘要
After got the scattered point cloud model from the 3D scanner, first search the K nearest neighbors for each point by constructing the K D tree; Second according to those neighborhood relationships, use the least square fitting planar method to estimate the normal vector of each point. Next determine the boundary of point cloud, select the extreme point as the initial point, and build seed triangle. Finally use the local optimal triangle mesh growing algorithm based on multiple constraints, start from the seed triangle, make the edge as extension condition, search for suitable point to construct new triangle layer by layer. During this process four constraints added, to better select the extension point, and extend the triangle edge outward, finally generate adjacent triangle meshes, realize the surface reconstruction more realistically.
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