• DocumentCode
    3207527
  • Title

    Elastic-string models for representation and analysis of planar shapes

  • Author

    Mio, Washington ; Srivastava, Anuj

  • Author_Institution
    Dept. of Math., Florida State Univ., Tallahassee, FL, USA
  • Volume
    2
  • fYear
    2004
  • fDate
    27 June-2 July 2004
  • Abstract
    We develop a new framework for the quantitative analysis of shapes of planar curves. Shapes are modeled on elastic strings that can be bent, stretched or compressed at different rates along the curve. Shapes are treated as elements of a space obtained as the quotient of an infinite-dimensional Riemannian manifold of elastic curves by the action of a reparameterization group. The Riemannian metric encodes the elastic properties of the string and has the property that reparameterizations act by isometrics. The geodesies in shape space are used to quantify shape dissimilarities, interpolate and extrapolate shapes, and align shapes according to their elastic properties. The shape spaces and metrics constructed offer a novel environment for the study of shape statistics and for the investigation and simulation of shape dynamics.
  • Keywords
    differential geometry; image representation; object recognition; statistical analysis; Riemannian metric; elastic-string models; infinite-dimensional Riemannian manifold; planar curve shapes; quantitative analysis; shape dissimilarities; Algorithm design and analysis; Deformable models; Image analysis; Infrared detectors; Interpolation; Magnetic resonance imaging; Mathematics; Shape; Statistical analysis; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-2158-4
  • Type

    conf

  • DOI
    10.1109/CVPR.2004.1315138
  • Filename
    1315138