• DocumentCode
    3402663
  • Title

    Surface extraction from binary volumes with higher-order smoothness

  • Author

    Lempitsky, Victor

  • Author_Institution
    Univ. of Oxford, Oxford, UK
  • fYear
    2010
  • fDate
    13-18 June 2010
  • Firstpage
    1197
  • Lastpage
    1204
  • Abstract
    A number of 3D shape reconstruction algorithms, in particular 3D image segmentation methods, produce their results in the form of binary volumes, where a binary value indicates whether a voxel is associated with the interior or the exterior. For visualization purpose, it is often desirable to convert a binary volume into a surface representation. Straightforward extraction of the median isosurfaces for binary volumes using the marching cubes algorithm, however, produces jaggy, visually unrealistic meshes. Therefore, similarly to some previous works, we suggest to precede the isosurface extraction by replacing the original binary volume with a new continuous-valued embedding function, so that the zero-isosurface of the embedding function is smooth but at the same time consistent with the original binary volume. In contrast to previous work, computing such an embedding function in our case permits imposing a higher-order smoothness on the embedding function and involves solving a convex optimization problem. We demonstrate that the resulting separating surfaces are smoother and of better visual quality than minimal area separating surfaces extracted by previous approaches to the problem. The code of the algorithm is publicly available.
  • Keywords
    feature extraction; image reconstruction; image segmentation; optimisation; smoothing methods; 3D image segmentation methods; 3D shape reconstruction algorithms; binary volumes; continuous-valued embedding function; convex optimization problem; embedding function; higher-order smoothness; isosurface extraction; marching cubes algorithm; surface extraction; surface representation; visualization purpose; Computer vision; Data mining; Embedded computing; Image converters; Image segmentation; Isosurfaces; Reconstruction algorithms; Shape; Surface reconstruction; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4244-6984-0
  • Type

    conf

  • DOI
    10.1109/CVPR.2010.5539832
  • Filename
    5539832