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Proceedings Paper

An algorithm of fast index constructing and neighbor searching for 3D LiDAR data
Author(s): YiCong Feng; MinYi Cen; TongGang Zhang; YiCong Feng
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Paper Abstract

As the 3D point-cloud data increase greatly with the development of data acquisition technology, it is an important prerequisite to establish an efficient index constructing and neighbor searching algorithm for point-cloud in data processing. In this paper, an efficient algorithm of index constructing and neighbor searching for 3D LiDAR data was proposed based on the combination of 3D grid, linear octree and Hash table. An experiment was conducted about the 3D LiDAR data and the result shows that the proposed method has higher efficiency of data index constructing and neighbor searching for 3D point-cloud acquired by mobile LiDAR.

Paper Details

Date Published: 19 March 2013
PDF: 6 pages
Proc. SPIE 8762, PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering, 87620Y (19 March 2013); doi: 10.1117/12.2019658
Show Author Affiliations
YiCong Feng, Southwest Jiaotong Univ. (China)
Information Ctr. of Land and Resources Dept. (China)
MinYi Cen, Southwest Jiaotong Univ. (China)
TongGang Zhang, Southwest Jiaotong Univ. (China)
YiCong Feng, Southwest Jiaotong Univ. (China)


Published in SPIE Proceedings Vol. 8762:
PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering
Honghua Tan, Editor(s)

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