大规模点云内外存调度绘制技术

In-core and Out-of-core Exchange Rendering Technique of Large-scale Point Cloud

为实现大规模点云的快速绘制,提出以部分内存访问机制为基础、以节点点数上限为叶节点形成条件的平衡八叉树存储结构。设计点云内外存调度绘制流程,包括节点可见性判断、内外存数据调度和点云绘制等环节。为提高可见性判断的效率,在视点与节点距离、夹角约束条件的基础上给出节点可视半径约束。利用实测大规模点云数据进行实验,结果证明,该技术可以在有限的内存资源条件下,以较小的内存消耗实现上亿级规模点云从整体到局部的流畅绘制。

For fast rendering of large scale point cloud, balanced octree storage structure is proposed based on part-memory access mechanism and node points limit as leaf nodes forming condition. The rendering process in-core and out-of-core is designed, including node visible judgment, data scheduling and point cloud drawing. In order to improve the efficiency of visibility judgment, node visualization radius is proposed on the basis of distance and angle constraints between viewpoint and node. Experiments are done with measured large-scale point cloud data. It concludes that the technical approach in this paper is able to smoothly render one hundred million point cloud from global to local with a smaller memory consumption in limited memory resources.