Free-Form Surface Description in Multiple Scales: Extension to Incomplete Surfaces

  • Nasser Khalili
  • Farzin Mokhtarian
  • Peter Yuen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1689)


A novel technique for multi-scale smoothing of a free-form 3-D surface is presented. Diffusion of the surface is achieved through convolutions of local parametrisations of the surface with a 2-D Gaussian filter. Our method for local parametrisation makes use of semigeodesic coordinates as a natural and efficient way of sampling the local surface shape. The smoothing eliminates the surface noise together with high curvature regions such as sharp edges, therefore, sharp corners become rounded as the object is smoothed iteratively. During smoothing some surfaces can become very thin locally. Application of decimation followed by refinement removes very small/ thin triangles and segments those surfaces into parts which are then smoothed separately. Furthermore, surfaces with holes and surfaces that are not simply connected do not pose any problems. Our method is also more efficient than those techniques since 2-D rather than 3-D convolutions are employed. It is also argued that the proposed technique is preferable to volumetric smoothing or level set methods since it is applicable to incomplete surface data which occurs during occlusion. Our technique was applied to closed as well as open 3-D surfaces and the results are presented here.


Object Recognition Local Parametrisation Machine Intelligence Triangular Mesh Range Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Nasser Khalili
    • 1
  • Farzin Mokhtarian
    • 1
  • Peter Yuen
    • 1
  1. 1.Centre for Vision, Speech, and Signal Processing Department of Electronic and Electrical EngineeringUniversity of SurreyGuildfordUK

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