A recognition method about lidar data based on the rough set

Author

Zhang Yi ; Fu Mengyin ; Wang Meiling ; Xu Qian

Author_Institution

Sch. of Autom., Beijing Inst. of Technol., Beijing, China

fYear

2014

fDate

28-30 July 2014

Firstpage

8402

Lastpage

8407

Abstract

This paper analyzes how to achieve the accuracy of the lidar data processing. In this paper, we analyze the ways about classification of the point cloud data and extraction of the attribute feature data. We find a way on attaching attribute information to the point cloud data sets. At last, we use rough set algorithm to excavate clustering rules from a large number of the point cloud data. We achieved the point cloud data clustering by the method of rough set, and completed the recognition of obstacles.

Keywords

data mining; electrical engineering computing; feature extraction; optical radar; pattern classification; pattern clustering; rough set theory; LIDAR data; LIDAR data processing; attribute feature data extraction; attribute information; clustering rule excavation; obstacle recognition method; point cloud data clustering; point cloud data set classification; rough set algorithm; Automation; Data mining; Educational institutions; Electronic mail; Feature extraction; Laser radar; Three-dimensional displays; Data Mining; Point Cloud Data; Rough Set;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2014 33rd Chinese

Conference_Location

Nanjing

Type

conf

DOI

10.1109/ChiCC.2014.6896410

Filename

6896410