Research on Organizing Massive 3D Laser Point Cloud Data
In the paper, massive 3 D 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.
vehicular laser scanning system massive point cloud data quadtree
Xudong Xu Lei Wang
Beijing University of Technology, China
国际会议
三亚
英文
670-676
2015-12-26（万方平台首次上网日期，不代表论文的发表时间）