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Research on Organizing Massive 3D Laser Point Cloud Data

被引：0
|
作者：
Xu, Xudong [1 ]
Wang, Lei [1 ]
机构：
[1] Beijing Univ Technol, Beijing, Peoples R China
来源：
2015 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING APPLICATIONS (CSEA 2015) | 2015年
关键词：
vehicular laser scanning system; massive point cloud data; quadtree;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
In the paper, massive 3D laser point cloud data is obtained through vehicular laser scanning system. Massive 3D laser point cloud data is characterized by large data size, uneven distribution, complex data attributes, etc., and these characteristics are analyzed. Compared with traditional quadtree algorithm for processing, it is proposed that massive 3D laser point cloud data can be organized through utilizing improved quadtree algorithm. Characteristics of Hilbert curve are combined for further improving organization efficiency of massive 3D laser point cloud data on the basis of improved algorithm. In the paper, related experiment is implemented on corresponding platform with java language. Experiment proves that point cloud data is organized through improved quadtree algorithm. Efficiency is correspondingly improved compared with traditional quadtree algorithm. The improved algorithm is combined with Hibert curve synchronously for further improving organization efficiency.
引用
收藏
页码：670 / 676
页数：7
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