A comparison of 3D R-tree and octree to index large point clouds from a 3D terrestrial laser scanner

Soohee Han, Seongjoo Lee, Sang Pill Kim, Changjae Kim, Joon Heo, Heebum Lee

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

The present study introduces a comparison between 3D R-tree and octree which are noticeable candidates to index large point clouds gathered from a 3D terrestrial laser scanner. A query method, which is to find neighboring points within given distances, was devised for the comparison, and time lapses for the query along with memory usages were checked. From tests conducted on point clouds scanned from a building and a stone pagoda, it was shown that octree has the advantage of fast generation and query while 3D R-tree is more memory-efficient. Both index and leaf capacity were revealed to be ruling factors to get the best performance of 3D R-tree, while the number of level was of octree.

Original languageEnglish
Pages (from-to)39-46
Number of pages8
JournalJournal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
Volume29
Issue number1
DOIs
Publication statusPublished - 2011 Jan 1

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All Science Journal Classification (ASJC) codes

  • Earth and Planetary Sciences(all)

Cite this

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A comparison of 3D R-tree and octree to index large point clouds from a 3D terrestrial laser scanner. / Han, Soohee; Lee, Seongjoo; Kim, Sang Pill; Kim, Changjae; Heo, Joon; Lee, Heebum.

In: Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 29, No. 1, 01.01.2011, p. 39-46.

Research output: Contribution to journalArticle

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