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Konferenzbeitrag

Dynamic Remeshing and Applications

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45679

Vorsatz,  Jens
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45303

Rössl,  Christian
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45449

Seidel,  Hans-Peter
Computer Graphics, MPI for Informatics, Max Planck Society;

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Zitation

Vorsatz, J., Rössl, C., & Seidel, H.-P. (2003). Dynamic Remeshing and Applications. In Proceedings: 8th ACM Symposium on Solid Modeling and Applications (SM-03) (pp. 167-175). New York, USA: ACM.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-2CC6-1
Zusammenfassung
Triangle meshes are a flexible and generally accepted boundary representation for complex geometric shapes. In addition to their geometric qualities and topological simplicity, \emph{intrinsic} qualities such as the shape of the triangles, their distribution on the surface and the connectivity are essential for many algorithms working on them. In this paper we present a flexible and efficient remeshing framework that improves these intrinsic properties while keeping the mesh geometrically close to the original surface. We use a particle system approach and combine it with an incremental connectivity optimization process to trim the mesh towards the requirements imposed by the user. The particle system uniformly distributes the vertices on the mesh, whereas the connectivity optimization is done by means of \emph{Dynamic Connectivity Meshes}, a combination of local topological operators that lead to a fairly regular connectivity. A dynamic skeleton ensures that our approach is able to preserve surface features, which are particularly important for the visual quality of the mesh. None of the algorithms requires a global parameterization or patch layouting in a preprocessing step but uses local parameterizations only. We also show how this general framework can be put into practice and sketch several application scenarios. In particular we will show how the users can adapt the involved algorithms in a way that the resulting remesh meets their personal requirements.