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Automatic and Interactive Mesh to T-Spline Conversion

Identifieur interne : 001139 ( Hal/Corpus ); précédent : 001138; suivant : 001140

Automatic and Interactive Mesh to T-Spline Conversion

Auteurs : Wan Chiu Li ; Nicolas Ray ; Bruno Lévy

Source :

RBID : Hal:inria-00105611

Abstract

In Geometry Processing, and more specifically in surface approximation, one of the most important issues is the automatic generation of a quad-dominant control mesh from an arbitrary shape (e.g. a scanned mesh). One of the first fully automatic solutions was proposed by Eck and Hoppe in 1996. However, in the industry, designers still use manual tools (see e.g. cyslice). The main difference between a control mesh constructed by an automatic method and the one designed by a human user is that in the second case, the control mesh follows the features of the model. More precisely, it is well known from approximation theory that aligning the edges with the principal directions of curvature improves the smoothness of the reconstructed surface, and this is what designers intuitively do. In this paper, our goal is to automatically construct a control mesh driven by the anisotropy of the shape, mimicking the mesh that a designer would create manually. The control mesh generated by our method can be used by a wide variety of representations (splines, subdivision surfaces...). We demonstrate our method applied to the automatic conversion from a mesh of arbitrary topology into a T-Spline surface. Our method first extracts an initial mesh from a PGP (Periodic Global Parameterization). To facilitate user-interaction, we extend the PGP method to take into account optional user-defined information. This makes it possible to locally tune the orientation and the density of the control mesh. The user can also interactively remove edges or sketch additional ones. Then, from this initial control mesh, our algorithm generates a valid T-Spline control mesh by enforcing some validity constraints. The valid T-Spline control mesh is finally fitted to the original surface, using a classic regularized optimization procedure. To reduce the L-infinity approximation error below a user-defined threshold, we iteratively use the T-Spline adaptive local refinement.

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Hal:inria-00105611

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