摘要
点云数据拟合是对点云数据处理的一个重要方法,针对传统最小二乘(LS)法对复杂点云拟合精度不高的缺点,采用一种基于移动最小二乘(MLS)法的点云数据拟合方法,应用于点云数据拟合,并与传统最小二乘(LS)比较,结果表明:移动最小二乘(MLS)法对复杂点云拟合结果具有精度高,可靠性强等优点,对复杂点云进行拟合时,移动最小二乘比于传统最小二乘(LS)法有优势。
Fitting of point cloud data is an important method in point cloud data processing. Aiming at the shortcomings of the traditional least squares（ LS） fitting which has low precision for complex point cloud,this paper uses a point cloud data fitting method based on moving least squares（ MLS） to fit the point cloud data. And comparing with the traditional least squares（ LS）,the results show that： The moving least squares（ MLS） has the advantages of higher precision,reliability and so on. Compared with the least squares（ LS）,the moving least squares has the advantages in the aspect of complex point cloud fitting.
出处
《勘察科学技术》
2016年第4期26-28,36,共4页
Site Investigation Science and Technology
关键词
移动最小二乘法
点云数据
权函数
moving least squares（MLS）
point cloud data
weight function
