计算机科学 ›› 2016, Vol. 43 ›› Issue (Z6): 175-178.doi: 10.11896/j.issn.1002-137X.2016.6A.041

• 模式识别与图像处理 • 上一篇    下一篇

三维激光点云数据的可视化研究

徐旭东,李泽   

  1. 北京工业大学计算机学院 北京100124,北京工业大学计算机学院 北京100124
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金:基于多维点云与配准影像的结构特征自动探测(41371434)资助

Visualization Research of Point Cloud Data in 3D Laser Scanning

XU Xu-dong and LI Ze   

  • Online:2018-12-01 Published:2018-12-01

摘要: 大量的点云数据是通过三维激光扫描得到的,而点云数据的显示快慢受到了数据索引的直接影响,这是一个基础性问题。经过研究,八叉树与叶节点KD树相结合的混合空间索引结构以及LOD构建的层次细节模型是用来解决点云数据管理与可视化效率不高的问题的有效方法。在局部,通过在叶子节点中构建的KD树实现高效的查询和显示;在全局,为了实现快速检索与调度使用了八叉树模型。采用这种混合数据模型进行点云组织,建立空间索引,并对点云数据进行LOD构建,实现了点云数据的高效检索以及可视化。

关键词: 八叉树,KD树,点云数据,可视化

Abstract: D laser scanning can obtain a lot of point cloud data,the display speed of which is directly affected by their structure.After the research,a spatial index structure mixing the octree and the leaf node of K-D tree,as well as a level detail (LOD) model is an efficient method to solve the problem of the low efficiency in managing and visualizing the point cloud data.Globally,quick indexing and management can be realized by the octree model.Locally,efficient query and display can be realized by the K-D tree constructed in memory.This mixed data model is adopted to organize point cloud,establish spatial index,and construct point cloud data by LOD,thereby realizing the index and visualization of point cloud data.

Key words: Octree,K-D tree,Point cloud data,Visualization

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