• 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