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Level of Detail Continuum for Huge Geometric Data

Abstract : In this paper we propose a unified solution for the creation of levels of detail on very large input data. We build a hierarchical signed distance function in an octree around the data and use this hierarchy to generate a continuum of levels of detail. Our distance function construction, based on the Gradient Vector Flow and the Poisson equation, builds on multigrid resolution algorithms. Using an appropriate interpolation scheme within the octree we obtain a continuous hierarchical distance function, which allows us to define a continuum of levels of detail for huge geometries. During this process, holes and undersampling issues in the input data are automatically corrected. We present three applications of our hierarchy: a novel hierarchical deformable model scheme that can automatically reconstruct closed Eulerian meshes of up to a million faces in a few minutes, an alternate distance-driven contouring approach, and raytracing of huge data models.
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Submitted on : Friday, May 19, 2006 - 8:33:00 PM
Last modification on : Thursday, January 20, 2022 - 4:15:18 PM
Long-term archiving on: : Tuesday, February 22, 2011 - 10:58:47 AM


  • HAL Id : inria-00070455, version 1


Florent Duguet, Carlos Henandez Esteban, George Drettakis, Francis Schmitt. Level of Detail Continuum for Huge Geometric Data. [Research Report] RR-5552, INRIA. 2006, pp.28. ⟨inria-00070455⟩



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