摘要
首先详细讨论了借助包围盒建立点云K邻域以及使用平面拟合方法获取法矢量等方法,然后根据点云数据法矢量变化程度,采用自适应八叉树得到压缩后的点云数据.对相关参数的选取以及算法步骤进行了改进.最后,使用此方法实现了点数为10000的点云模型的数据压缩.
Firstly, the establishment of K-nearest points by bounding box as well as calculation of the normal vectors by plane fitting was discussed in detail in this paper. Then,according to the change ratio of normal vector, octree-based compression method was proposed to obtain the compressed data. Some key parameters and algorithm were also improved in this paper. Finally, point cloud data which consist of 10 000 points was compressed by the methods.
出处
《河南科学》
2010年第10期1300-1304,共5页
Henan Science
基金
国家科技支撑计划课题(2006BAJ03A07)
关键词
点云压缩
K邻域
法向量拟合
八叉树
data compression
K-nearest points
normal vector fitting
octree
