• DocumentCode
    2614849
  • Title

    Determining 3-D object pose using the complex extended Gaussian image

  • Author

    Kang, Sing Bing ; Ikeuchi, Katsushi

  • Author_Institution
    Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    1991
  • fDate
    3-6 Jun 1991
  • Firstpage
    580
  • Lastpage
    585
  • Abstract
    A method based on the extended Gaussian image (EGI) which can be used to determine the pose of a 3-D object is presented. In this scheme, the weight associated with each outward surface normal is a complex weight. The normal distance of the surface from the predefined origin is encoded as the phase of the weight, while the magnitude of the weight is the visible area of the surface. This approach decouples the orientation and translation determination into two distinct least-squares problems. Experiments involving synthetic data of two polyhedral and two smooth objects as well as real range data of the same smooth objects indicate the feasibility of this method
  • Keywords
    computer vision; computerised pattern recognition; 3-D object pose; 3D object pose; ellipsoid; extended Gaussian image; least-squares problems; orientation; outward surface normal; range data; smooth objects; synthetic data; torus; translation determination; Computer vision; Data mining; Equations; H infinity control; Object recognition; Optimization methods; Orbital robotics; Prototypes; Robot kinematics; Robot vision systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1991. Proceedings CVPR '91., IEEE Computer Society Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-2148-6
  • Type

    conf

  • DOI
    10.1109/CVPR.1991.139757
  • Filename
    139757