Geometric primitive extraction from LiDAR-scanned point clouds

被引：0

作者：

Nakhoon Baek

Woo-seok Shin

Kuinam J. Kim

机构：

[1] Kyungpook National University,School of Computer Science and Engineering

[2] Kyonggi University,Department of Convergence Security

来源：

Cluster Computing | 2017年 / 20卷

关键词：

LiDAR; Light detection and ranging; Efficient processing; Geometric primitive; Point clouds;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Recently, we have lots of LiDAR (light detection and ranging) data, for applications of high-resolution maps including geography, geology, forestry, and others. One of the current research and industrial issues is efficient ways of storing the LiDAR data itself, and also elegant ways of extracting geometric primitives from those LiDAR-scanned 3D point clouds. In this paper, we first analyze the characteristics of LiDAR data and tis storage schemes. Additionally, we present an efficient method to extract geometric primitives from those point clouds. Its implementation and results are also presented.

引用

页码：741 / 748

页数：7