| 1. | A fast progressive surface reconstruction algorithm for unorganized points
散乱数据点的增量快速曲面重建算法 |
| 2. | An algorithm of searching topological structure from 3d unorganized points
寻找三维散乱数据点拓扑结构的一种算法 |
| 3. | A region - growing algorithm was proposed to reconstruct triangular meshes from unorganized point cloud
摘要提出一种对无规则点云进行三角网格重构的区域增长算法。 |
| 4. | Based on the theory of space dividing using envelopment - box , an algorithm to search topological relationship from 3d unorganized points is proposed in this thesis
本文提出了一种利用包围盒空间分割方法对散乱数据点点云进行空间分割进而寻求拓扑关系的方法。 |
| 5. | In this thesis , the surface reconstruction for unorganized points , and the design and implementation of the system for constructing the finite element mesh
本文主要在基于散乱点的三维重建算法，曲面有限元网格自动生成工具系统的设计和实现等方面进行了研究和探讨。 |
| 6. | Surface reconstruction method based on fea surface of 3d unorganized points is divided into four modes according to the special features of points on surface in this thesis
( 2 )基于有限元分析的曲面重构方法根据离散数据点的不同特点，本文将离散数据点曲面分成四种模型。 |
| 7. | We use a size changeable adjacent field to describe the topological structure of 3d unorganized points in our algorithm . it can offer essential dynamic information for tessellation and points " normal
算法采用可以控制大小的邻域作为空间散乱数据点的拓扑关系的几何描述，为网格划分和点的法向量的几何描述提供了必要的动态几何信息。 |
| 8. | The proposed algorithm is capable of handling with kinds of point clouds data , such as three dimensional unorganized point clouds , point clouds acquired from organized cad models or point clouds acquired from finite element analysis meshes
本文所提出的算法可以处理各种数据点云,包括三维散乱数据点云、规则cad模型离散后所获得的数据点云和由有限元网格采集到的数据点云。 |
| 9. | As it can be expressed easily by argument equations , we use the conicoid as the criteria of points " classification . based on the point ' s normal and the adjacent field , corresponding to the conicoid equation such as plane , ball and cylinder , we search the points that fit the equation along the adjacent field . using this method , we realized the automatic classification of unorganized points
本文采用了可以比较方便地用参数方程表示的二次曲面作为数据点的分类标准，根据点的法向量以及其邻域结点的各种属性，对应于平面、球面、柱面等二次曲面，依据曲面方程的特点，从起始点开始沿邻域深度优先递归寻找符合方程的数据点，实现了散乱数据点的自动分类。 |
| 10. | Based on data cloud , which is measured from 3 - coordinate measuring machine ( cmm ) or so , an algorithm to search lopological structure from 3d unorganized points using envelopment - box technology is proposed in this thesis . based on this method , we searching neighbor points of sampling point . we also improve the max - min angle criteria to realize local triangulation , and then get the normal of sampling point from the triangulation
本文以测量得到的曲面数据点点云为基础，提出了一种基于包围盒的自动寻找三维散乱数据点之间拓扑结构的方法，采用该方法寻找采样点的邻域结点，并对三角剖分中的典型优化准则?最小内角最大准则提出了改进，按照改进后的优化准则实现了采样点的局部三角划分，并进一步求解得到采样点的法向量，依据法向量及邻域拓扑关系在二次曲面的基础上实现了散乱数据曲面重构中的数据点的自动分类。 |
