Locality sensitive hashing for LiDAR data processing

Author

Zhan, Qingming ; Cai, Ying ; Liang, Yubin ; Xiao, Yinghui

Author_Institution

Sch. of Urban Design, Wuhan Univ., Wuhan, China

fYear

2011

fDate

24-26 June 2011

Firstpage

4145

Lastpage

4147

Abstract

Terrain modeling and building reconstruction requires interpretation of millions of points acquired by terrestrial and airborne laser scanners. Nearest neighbors search is often used in LiDAR data processing based computation of local features in 3D space. Kd-tree and range tree etc. are usually employed for range search. In this paper we investige the feasibility of Locality Sensitive Hashing (LSH) for processing LiDAR data by means of approximate nearest neighbors search. And comparison experiments with kd-tree demonstrate its effectiveness and performance for supervised classification of laser scanning points.

Keywords

data handling; geophysical image processing; image classification; remote sensing by radar; 3D space; Kd-tree; LIDAR data processing; airborne laser scanner; building reconstruction; laser scanning points; locality sensitive hashing; range tree; supervised classification; terrain modeling; terrestrial laser scanner; Data processing; Educational institutions; Laser modes; Laser radar; Laser theory; Nearest neighbor searches; Remote sensing; LiDAR; kd-tree; locality sensitive hashing; nearest neighbors search;

fLanguage

English

Publisher

ieee

Conference_Titel

Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on

Conference_Location

Nanjing

Print_ISBN

978-1-4244-9172-8

Type

conf

DOI

10.1109/RSETE.2011.5965160

Filename

5965160