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http://dx.doi.org/10.7848/ksgpc.2011.29.1.39

A Comparison of 3D R-tree and Octree to Index Large Point Clouds from a 3D Terrestrial Laser Scanner  

Han, Soo-Hee (연세대학교 사회환경시스템공학부)
Lee, Seong-Joo (연세대학교 컴퓨터과학과)
Kim, Sang-Pil (연세대학교 사회환경시스템공학부)
Kim, Chang-Jae (연세대학교 사회환경시스템공학부)
Heo, Joon (연세대학교 사회환경시스템공학부)
Lee, Hee-Bum (육군3사관학교 토목건축공학과)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.29, no.1, 2011 , pp. 39-46 More about this Journal
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 oetree.
Keywords
3D R-tree; Octree; Terrestrial Laser Scanner; Point Cloud; Query;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
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