• DocumentCode
    64591
  • Title

    Automated Extraction of 3-D Railway Tracks from Mobile Laser Scanning Point Clouds

  • Author

    Bisheng Yang ; Lina Fang

  • Author_Institution
    State Key Lab. of Inf. Eng. in Surveying, Mapping, & Remote Sensing, Wuhan Univ., Wuhan, China
  • Volume
    7
  • Issue
    12
  • fYear
    2014
  • fDate
    Dec. 2014
  • Firstpage
    4750
  • Lastpage
    4761
  • Abstract
    The demand for automated railway tracks extraction is driven by the importance of maintaining and updating the fundamental geographic data of railway tracks for railway engineering. Mobile laser scanning (MLS), which is a promising technology for the rapid 3-D mapping of railways, provides a good means to capture details along the corridors, including tracks, clearance of overhanging wires, natural obstructions (e.g., trees and rock faces), and tunnel/bridge clearances. This paper presents an automated method to detect tracks from MLS point clouds. Both the geometry and intensity data of railway tracks are utilized to extract track points and to model tracks. Experiments were undertaken to evaluate the validity of the proposed method based on the test dataset captured by Optech´s Lynx Mobile Mapper System, proving it a promising solution to extract 3-D tracks from MLS point clouds.
  • Keywords
    geometry; geophysical techniques; optical scanners; optical tracking; railway engineering; 3D automated railway track extraction; MLS; Optech Lynx mobile mapper system; data intensity; geographic data; geometry; mobile laser scanning point cloud; natural obstruction; railway engineering; rapid 3D railway mapping; track detection; tunnel-bridge clearance; Data mining; Electronic ballasts; Feature extraction; Rail transportation; Roads; Three-dimensional displays; Intensity feature; mobile laser scanning (MLS); pattern recognition; scanning lines; track extraction;
  • fLanguage
    English
  • Journal_Title
    Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    1939-1404
  • Type

    jour

  • DOI
    10.1109/JSTARS.2014.2312378
  • Filename
    6783695