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Conference Paper Distance Based Neighbor Correlation for the Segmentation
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Authors
Ki-In Na, Jaemin Byun, Myoungchan Roh, Bumsoo Seo
Issue Date
2013-10
Citation
International Conference on Ubiquitous Robots and Ambient Intelligence (URAI) 2013, pp.211-214
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/URAI.2013.6677344
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. © 2013 IEEE.
KSP Keywords
3D Lidar, Distance-based, Normal vector, Real data, Segmentation of point cloud, Simulation data, local convexity