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Efficient Spherical Parametrization Using Progressive Optimization

  • Shenghua Wan
  • Tengfei Ye
  • Maoqing Li
  • Hongchao Zhang
  • Xin Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7633)

Abstract

Spherical mapping is a key enabling technology in modeling and processing genus-0 close surfaces. A closed genus-0 surface can be seamless parameterized onto a unit sphere. We develop an effective progressive optimization scheme to compute such a parametrization, minimizing a nonlinear energy balancing angle and area distortions. Among all existing state-of-the-art spherical mapping methods, the main advantage of our spherical mapping are two-folded: (1) the algorithm converges very efficiently, therefore it is suitable for handling huge geometric models, and (2) it generates bijective and lowly distorted mapping results.

Keywords

Spherical Parametrization Hierarchical Optimization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Shenghua Wan
    • 1
  • Tengfei Ye
    • 2
  • Maoqing Li
    • 2
  • Hongchao Zhang
    • 3
  • Xin Li
    • 1
  1. 1.School of Electrical Engineering and Computer ScienceLouisiana State University (LSU)Baton RougeUSA
  2. 2.Department of AutomationXiamen UniversityXiamenChina
  3. 3.Department of MathematicsLSUBaton RougeUSA

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