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.
|Number of pages||8|
|Journal||Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography|
|Publication status||Published - 2011|
All Science Journal Classification (ASJC) codes
- Earth and Planetary Sciences(all)