• DocumentCode
    2551883
  • Title

    3-D Scene Modelling from Multiple Images using Radial Basis Function Networks

  • Author

    Grum, Matthew ; Bors, Adrian G.

  • Author_Institution
    Dept. of Comput. Sci., Univ. of York, York
  • fYear
    2007
  • fDate
    27-29 Aug. 2007
  • Firstpage
    105
  • Lastpage
    110
  • Abstract
    A new approach for modelling multiple 3-D objects from a sparse set of images taken from various viewpoints is proposed in this paper. A voxel model of the scene is estimated from the given set of images using the space carving algorithm. An implicit radial basis function (RBF) network is used afterwards to model the voxel data. The multiorder function is chosen as the kernel function due to its property of enforcing smoothing constraints in the first three derivatives. A suitable initialization is proposed for the RBF parameters. Displacements of surface patches along epipolar lines are used to update the centers of basis functions leading to the modelling errors minimization. The proposed method is used to model a complex 3-D scene.
  • Keywords
    image reconstruction; image representation; radial basis function networks; smoothing methods; solid modelling; 3D scene modelling; RBF network; epipolar lines; image representation; kernel function; multiorder function; multiple images; radial basis function network; scene reconstruction; smoothing method; space carving algorithm; surface displacement; voxel model; Cameras; Computer science; Electronic mail; Error correction; Image reconstruction; Interpolation; Kernel; Layout; Radial basis function networks; Smoothing methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing, 2007 IEEE Workshop on
  • Conference_Location
    Thessaloniki
  • ISSN
    1551-2541
  • Print_ISBN
    978-1-4244-1565-6
  • Electronic_ISBN
    1551-2541
  • Type

    conf

  • DOI
    10.1109/MLSP.2007.4414290
  • Filename
    4414290