DocumentCode
3087811
Title
Automatic road extraction from mobile laser scanning data
Author
Hanyun Wang ; Zhipeng Cai ; Huan Luo ; Cheng Wang ; Peng Li ; Wentao Yang ; Suoping Ren ; Li, Jie
Author_Institution
Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
fYear
2012
fDate
16-18 Dec. 2012
Firstpage
136
Lastpage
139
Abstract
Extraction of road surface and boundary is essential for autonomous vehicle navigation, road monitoring and important scene structures extraction. Mobile laser scanning (MLS) technology as a new information acquiring manner can quickly scan the whole scene and provide density and accurate 3D coordinate data and other information such as trajectory, color and reflectance. In this paper an automatic road extraction method is proposed based on trajectory information from mobile laser scanning data. Through the trajectory, location and approximated direction of local road patch could be determined. Searching algorithm is applied along the approximated road direction and the orthogonal direction. To determine the road boundary, a hypothesis testing method based on local altitude variance is used. To filter false boundary points, local altitude mean value is applied. Experiment results demonstrate the reliability of the proposed algorithm for automatic road surface and boundary extraction.
Keywords
feature extraction; image colour analysis; monitoring; optical scanners; road traffic; road vehicles; search problems; statistical analysis; 3D coordinate data; MLS technology; automatic road surface extraction; autonomous vehicle navigation; color information; density; hypothesis testing method; local altitude mean value; local altitude variance; local road patch; mobile laser scanning data; reflectance; reliability; road boundary extraction; road monitoring; scene scan; scene structure extraction; searching algorithm; trajectory information; Global Navigation Satellite Systems; Lasers; Reliability; Trajectory; mobile laser scanning (MLS); road extraction; trajectory;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision in Remote Sensing (CVRS), 2012 International Conference on
Conference_Location
Xiamen
Print_ISBN
978-1-4673-1272-1
Type
conf
DOI
10.1109/CVRS.2012.6421248
Filename
6421248
Link To Document