A classification method for building detection based on LiDAR point clouds

Author

Zhou Mei ; Xia Bing ; Su Guozhong ; Tang Lingli ; Li Chanrong

Author_Institution

Sky-To-Earth Syst. of Syst., Chinese Acad. of Sci., Beijing, China

fYear

2009

fDate

20-22 May 2009

Firstpage

1

Lastpage

5

Abstract

Building detection using LiDAR data is a popular topic in LiDAR data processing. The object classification can play an important role in the detection. In this paper, a new algorithm based on LiDAR point clouds is developed to resolve the object classification difficulties in the case of trees close to buildings. Compared with other algorithms, the methods can work effectively due to use the combination of height texture and regular geometric element. The experiment results is also given and discussed to improve the validity of the proposed algorithm.

Keywords

building; geophysical techniques; image classification; object detection; optical radar; remote sensing by radar; vegetation; LIght Detection And Ranging; building detection; data processing; height texture; image classification; lidar point cloud; object classification; remote sensing; trees; Classification algorithms; Classification tree analysis; Clouds; Data processing; Event detection; Image segmentation; Laser radar; Object detection; Optical pulses; Vegetation mapping;

fLanguage

English

Publisher

ieee

Conference_Titel

Urban Remote Sensing Event, 2009 Joint

Conference_Location

Shanghai

Print_ISBN

978-1-4244-3460-2

Electronic_ISBN

978-1-4244-3461-9

Type

conf

DOI

10.1109/URS.2009.5137608

Filename

5137608