• DocumentCode
    2205233
  • Title

    Towards reliable fusion of segmented surface descriptions

  • Author

    Fischer, Daniel ; Kohlhepp, Peter

  • Author_Institution
    Inst. fur Angewandte Inf., Forschungszentrum Karlsruhe, Germany
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    405
  • Abstract
    This paper presents a novel solution for integrating range views into 3D geometry models. Unlike previous approaches, sparse surface and relation attributes are fused directly, without relying on the original range data or a dense mesh of data points. Corresponding surface patches in overlapping views are found and registered automatically. The main focus is on the integration of registered views. Two algorithms for merging partial boundary polygons, one following the `explained´ and the other following the `enlarging´ contour, are presented and methods for updating surface areas, quadric approximations and other attributes are provided. The technique is relevant for 3D map making in autonomous vehicles: the current surface map is used for symbolic action planning while being extended by incoming sensor data. Preliminary experimental results indicate that the prototype system copes well with large measurement and segmentation errors
  • Keywords
    computational geometry; image reconstruction; 3D geometry models; 3D map making; autonomous vehicles; enlarging contour; explained contour; incoming sensor data; large measurement errors; large segmentation errors; overlapping views; partial boundary polygon merging; quadric approximations; range views; registered views; reliable segmented surface description fusion; sparse relation attributes; sparse surface attributes; surface areas; surface patches; symbolic action planning; Image reconstruction; Image segmentation; Information geometry; Merging; Mobile robots; Prototypes; Remotely operated vehicles; Sensor phenomena and characterization; Solid modeling; Surface reconstruction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2000. Proceedings. IEEE Conference on
  • Conference_Location
    Hilton Head Island, SC
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-0662-3
  • Type

    conf

  • DOI
    10.1109/CVPR.2000.854862
  • Filename
    854862