Parametrization and smooth approximation of surface triangulations
Computer Aided Geometric Design
Smooth surface reconstruction via natural neighbour interpolation of distance functions
Proceedings of the sixteenth annual symposium on Computational geometry
Conformal Surface Parameterization for Texture Mapping
IEEE Transactions on Visualization and Computer Graphics
Generalized barycentric coordinates on irregular polygons
Journal of Graphics Tools
Non-distorting Flattening for Virtual Colonoscopy
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Scattered Data Techniques for Surfaces
Dagstuhl '97, Scientific Visualization
Shrouds: optimal separating surfaces for enumerated volumes
VISSYM '03 Proceedings of the symposium on Data visualisation 2003
Computer Aided Geometric Design
MC*: Star Functions for Marching Cubes
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Conformal virtual colon flattening
Proceedings of the 2006 ACM symposium on Solid and physical modeling
Lifting curve parameterization methods to isosurfaces
Computer Aided Geometric Design
IEEE Transactions on Visualization and Computer Graphics
Spherical parameterization of marching cubes IsoSurfaces based upon nearest neighbor coordinates
Journal of Computer Science and Technology
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The triangular mesh surfaces (TMS) which result form the Marching Cubes (MC) algorithm have some unique and special properties not shared by general TMS. We exploit some of these properties in the development of some new, effective and efficient methods for parameterizing these surfaces. The parameterization consists of a planar triangulation which is isomorphic (maps one-to-one) to the triangular mesh. The parameterization is computed as the solution of a sparse linear system of equations which is based upon the fact that locally the MC surfaces are functions (height-fields). The coefficients of the linear system utilize natural neighbor coordinates (NNC) which depend upon Dirchlet tessellations. While the use of NNC for general TMS can be somewhat computationally expensive and is often done procedurally, for the present case of MC surfaces, we are able to obtain simple and explicit formulas which lead to efficient computational algorithms.