• DocumentCode
    3158825
  • Title

    A novel method for segmentation of cones and cylinders from geometrically fused depth maps

  • Author

    Ng, I. ; Illingworth, J. ; Jones, G.

  • Author_Institution
    Surrey Univ., Guildford, UK
  • fYear
    1995
  • fDate
    4-6 Jul 1995
  • Firstpage
    544
  • Lastpage
    548
  • Abstract
    The difficult problem of extraction of cylindrical and conic surfaces from range data is considered. A new method based on taking pairs of surface patches and generating and accumulating curved surface parameters is presented. Parameter clusters are identified by a hierarchical scheme using an unsupervised clustering method. The method is able to work with sparse or dense data and does not require image format data. It can therefore be applied to geometrically fused 3D data taken from multiple views. The method is shown to work well in complicated scenes which include significant occlusion. The benefits of multiple view fusion are shown by experiment
  • Keywords
    feature extraction; image segmentation; parameter estimation; sensor fusion; cones; curved surface parameters; cylinders; dense data; experiment; geometrically fused 3D data; geometrically fused depth maps; hierarchical scheme; image segmentation; multiple view fusion; multiple views; occlusion; parameter clusters; parameter estimation; range data; sparse data; surface patches; unsupervised clustering method;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Image Processing and its Applications, 1995., Fifth International Conference on
  • Conference_Location
    Edinburgh
  • Print_ISBN
    0-85296-642-3
  • Type

    conf

  • DOI
    10.1049/cp:19950718
  • Filename
    465504