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The Visual Computer

, Volume 28, Issue 5, pp 493–509 | Cite as

Using surface variability characteristics for segmentation of deformable 3D objects with application to piecewise statistical deformable model

  • Peng DuEmail author
  • Horace H. S. Ip
  • Bei Hua
  • Jun Feng
Original Article

Abstract

To cope with the small sample size problem in the construction of Statistical Deformable Models (SDM), this paper proposes two novel measures that quantify the similarity of the variability characteristics among deforming 3D meshes. These measures are used as the basis of our proposed technique for partitioning a 3D mesh for the construction of piecewise SDM in a divide-and-conquer strategy. Specifically, the surface variability information is extracted by performing a global principal component analysis on the set of sample meshes. An iterative face clustering algorithm is developed for segmenting a mesh that favors grouping triangular faces having similar variability characteristics into a same mesh component. We apply the proposed mesh segmentation algorithm to the construction of piecewise SDM and evaluate the representational ability of the resulting piecewise SDM through the reconstruction of unseen meshes. Experimental results show that our approach outperforms several state-of-the-art methods in terms of the representational ability of the resulting piecewise SDM as evaluated by the reconstruction accuracy.

Keywords

Mesh segmentation Principal component analysis Statistical deformable model Surface reconstruction 

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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Peng Du
    • 1
    • 2
    Email author
  • Horace H. S. Ip
    • 1
  • Bei Hua
    • 2
  • Jun Feng
    • 3
  1. 1.Department of Computer ScienceCity University of Hong Kong and USTC-CityU Joint Advanced Research CentreSuzhouP.R. China
  2. 2.School of Computer Science and TechnologyUniversity of Science and Technology of China and USTC-CityU Joint Advanced Research CentreSuzhouP.R. China
  3. 3.School of Information TechnologyNorthwest UniversityXi’anP.R. China

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