• DocumentCode
    2714574
  • Title

    A novel approach to extracting street lamps from vehicle-borne laser data

  • Author

    Hu, Yujie ; Li, Xiang ; Xie, Jun ; Guo, Lei

  • Author_Institution
    Key Lab. of Geogr. Inf. Sci., East China Normal Univ., Shanghai, China
  • fYear
    2011
  • fDate
    24-26 June 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The role of laser scanning technology in data collection and virtual environment modeling has been long recognized, especially for vehicle-borne laser scanning system (VBLS) which consists of a vehicle equipped with laser range scanners, CCD cameras and positioning devices. Up to now, most researches on vehicle-borne laser data are focused on the extractions of buildings, trees, etc., in correspondence with that on airborne LiDAR data. In this paper, instead, extraction of street lamps becomes our objective and a novel approach is proposed to fulfill it. An experiment is conducted to validate the proposed approach. Comparing with the images collected by the VBLS and real scenario observed from field work, the result indicates that the proposed approach is valid for extracting street lamps in terms of the accuracy of positioning and modeling ground targets.
  • Keywords
    airborne radar; geographic information systems; optical radar; optical scanners; virtual reality; CCD cameras; airborne LiDAR data; building extractions; data collection; ground target modeling; ground target positioning; laser range scanners; laser scanning technology; positioning devices; street lamp extraction; tree extractions; vehicle-borne laser data; vehicle-borne laser scanning system; virtual environment modeling; Cameras; Global Positioning System; Laser modes; Roads; Vehicles; Geographic Information System (GIS); density of projected points (DoPP); distance data; street lamps extraction; vehicle-borne laser scanning (VBLS);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2011 19th International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    2161-024X
  • Print_ISBN
    978-1-61284-849-5
  • Type

    conf

  • DOI
    10.1109/GeoInformatics.2011.5981183
  • Filename
    5981183