Geometric primitive extraction from LiDAR-scanned point clouds

被引：4

作者：

Baek, Nakhoon ^{[1
]}

Shin, Woo-Seok ^{[1
]}

Kim, Kuinam J. ^{[2
]}

机构：

[1] Kyungpook Natl Univ, Sch Comp Sci & Engn, Taegu 41566, South Korea

[2] Kyonggi Univ, Dept Convergence Secur, Suwon 16227, South Korea

来源：

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2017年 / 20卷 / 01期

基金：

新加坡国家研究基金会;

关键词：

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

D O I：

10.1007/s10586-017-0759-x

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

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：8

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