DocumentCode
651091
Title
Distance based neighbor correlation for the segmentation
Author
Ki-In Na ; Jaemin Byun ; Myoungchan Roh ; Bumsoo Seo
Author_Institution
Intell. Cognitive Res. Dept., ETRI, Daejeon, South Korea
fYear
2013
fDate
Oct. 30 2013-Nov. 2 2013
Firstpage
211
Lastpage
214
Abstract
This paper introduces the segmentation of point cloud with the distance-based connectivity that is originated from the connectivity of local convexity criterion to enhance its accuracy and singularity [1]. The proposed feature is applied to calculate the weighted normal vector and to partition ground and objects respectively through integrating it with other features. The performances of segmentations with the introduced criterion are demonstrated with the labeled simulation data and the real data from 3D LIDAR compared to the original connectivity.
Keywords
image segmentation; optical radar; radar imaging; 3D LIDAR; accuracy enhancement; distance based neighbor correlation; distance-based connectivity; local convexity criterion; point cloud segmentation; region growing algorithm; singularity enhancement; weighted normal vector; 3D LIDAR; autonomous vehicle; outdoor navigation; segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Ubiquitous Robots and Ambient Intelligence (URAI), 2013 10th International Conference on
Conference_Location
Jeju
Print_ISBN
978-1-4799-1195-0
Type
conf
DOI
10.1109/URAI.2013.6677344
Filename
6677344
Link To Document