Journal
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
Volume 20, Issue 1, Pages 741-748Publisher
SPRINGER
DOI: 10.1007/s10586-017-0759-x
Keywords
LiDAR; Light detection and ranging; Efficient processing; Geometric primitive; Point clouds
Funding
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education, Science and Technology [2016R1D1A3B03935488]
- Technology Innovation Development program (project name: Development of 3D GIS Platform for the LiDAR Data Utilization) - Small and Medium Business Administration, Korea [S2306348]
- Korea Technology & Information Promotion Agency for SMEs (TIPA) [S2306348] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
Ask authors/readers for more resources
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.
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