应 申, 毛政元, 李 霖, 许 光. 利用3D Voronoi图的兔子点云聚类分割[J]. 武汉大学学报 ( 信息科学版), 2013, 38(3): 358-361.
引用本文: 应 申, 毛政元, 李 霖, 许 光. 利用3D Voronoi图的兔子点云聚类分割[J]. 武汉大学学报 ( 信息科学版), 2013, 38(3): 358-361.
YING Shen, MAO Zhengyuan, LI Lin, XU Guang. Point Cloud Segmentation of 3D Rabbit Base 3D Voronoi[J]. Geomatics and Information Science of Wuhan University, 2013, 38(3): 358-361.
Citation: YING Shen, MAO Zhengyuan, LI Lin, XU Guang. Point Cloud Segmentation of 3D Rabbit Base 3D Voronoi[J]. Geomatics and Information Science of Wuhan University, 2013, 38(3): 358-361.

利用3D Voronoi图的兔子点云聚类分割

Point Cloud Segmentation of 3D Rabbit Base 3D Voronoi

  • 摘要: 利用基于3D Voronoi多面体分割三维空间,并将其应用于具有典型三维特征的点云数据的聚类分割。通过对点云数据的离散体元表示,透过Voronoi单元的特征参数实现了三维点集的度量、提取和结构分析,揭示了点集间存在的相互关系,并通过3D Voronoi图所确定的空间邻近关系完成点集间相似度的测度和聚类。以三维兔子点云为样本数据的实验分析表明,本文所提出的思路聚类分割特征明显。

     

    Abstract: 3D point pattern of cluster analysis is presented based on 3D Voronoi. 3D Voronoi cell is used to represent the spatial region that the spatial point effects. Through a quantitative description of the spatial parameters about 3D Voronoi cell there exists the potential to distinguish the weight and effective quantity of each point in the 3D space. Spatial neighborhood relationship among points is extracted according to 3D Voronoi cells to delimit the candidate points that will be clustered. The method illustrates segmentation and cluster distribution of 3D points based on the underlying density and spatial relationships, and actual analysis is imposed on the point cloud of 3D rabbit (Bunny). The ability to make quantitative description of each 3D Voronoi cell gives insights into spatial controls and cluster process on 3D points.

     

/

返回文章
返回