• DocumentCode
    34418
  • Title

    Building Reconstruction From High-Resolution Multiview Aerial Imagery

  • Author

    Bin Wu ; Xian Sun ; Qichang Wu ; Menglong Yan ; Hongqi Wang ; Kun Fu

  • Author_Institution
    Key Lab. of Technol. in Geo-Spatial Inf. Process. & Applic. Syst., Beijing, China
  • Volume
    12
  • Issue
    4
  • fYear
    2015
  • fDate
    Apr-15
  • Firstpage
    855
  • Lastpage
    859
  • Abstract
    In this letter, we propose a novel method to reconstruct accurate building structures from high-resolution multiview aerial imagery, using layered contour fitting (LCF) with a density-based clustering algorithm. Initially, the complicated 3-D scene is reconstructed by a probabilistic volumetric modeling algorithm. Subsequently, the reconstructed 3-D scene model is projected into layer images based on the height information. At last, we combine an extended layered density-based clustering approach with a generative LCF approach to remove noise and extract accurate building contours in every layer image at the same time. The final accurate 3-D building model is generated from these contours in layer images with a smoothing operation. Experiments on the aerial image sets demonstrate effectiveness and precision of our method.
  • Keywords
    building; curve fitting; feature extraction; geophysical image processing; image reconstruction; image resolution; natural scenes; pattern clustering; smoothing methods; solid modelling; 3D building model; 3D scene model reconstruction; building contour extraction; building structure reconstruction; extended layered density-based clustering approach; generative LCF approach; high resolution multiview aerial imagery; image smoothing; layer images; layered contour fitting; probabilistic volumetric modeling algorithm; Buildings; Clustering algorithms; Image reconstruction; Noise; Probabilistic logic; Solid modeling; Surface reconstruction; Building reconstruction; contour fitting; density-based clustering; probabilistic volumetric modeling;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2014.2364309
  • Filename
    6951411