• DocumentCode
    1605113
  • Title

    Surface registration by matching oriented points

  • Author

    Johnson, Andrew Edie ; Hebert, Martial

  • Author_Institution
    Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    1997
  • Firstpage
    121
  • Lastpage
    128
  • Abstract
    For registration of 3-D free-form surfaces we have developed a representation which requires no knowledge of the transformation between views. The representation comprises descriptive images associated with oriented points on the surface of an object. Constructed using single point bases, these images are data level shape descriptions that are used for efficient matching of oriented points. Correlation of images is used to establish point correspondences between two views; from these correspondences a rigid transformation that aligns the views is calculated. The transformation is then refined and verified using a modified iterative closest point algorithm. To demonstrate the generality of our approach, we present results from multiple sensing domains
  • Keywords
    image matching; image registration; image representation; iterative methods; object recognition; 3D free-form surface registration; data level shape descriptions; descriptive images; image correlation; image representation; iterative closest point algorithm; multiple sensing; object surface; oriented point matching; single point bases; view transformation; Contracts; Histograms; Indexing; Iterative closest point algorithm; Layout; Robot kinematics; Robot sensing systems; Shape; US Department of Energy; Voting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    3-D Digital Imaging and Modeling, 1997. Proceedings., International Conference on Recent Advances in
  • Conference_Location
    Ottawa, Ont.
  • Print_ISBN
    0-8186-7943-3
  • Type

    conf

  • DOI
    10.1109/IM.1997.603857
  • Filename
    603857