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Texture mapping progressive meshes
Author(s) -
Pedro V. Sander,
John Snyder,
Steven J. Gortler,
Hugues Hoppe
Publication year - 2001
Publication title -
digital access to scholarship at harvard (dash) (harvard university)
Language(s) - English
Resource type - Conference proceedings
ISBN - 1-58113-374-X
DOI - 10.1145/383259.383307
Subject(s) - polygon mesh , parametrization (atmospheric modeling) , texture atlas , heuristics , computer science , parametric statistics , algorithm , sequence (biology) , texture mapping , planarity testing , texture filtering , texture (cosmology) , surface (topology) , mathematics , artificial intelligence , mathematical optimization , geometry , image texture , computer graphics (images) , segmentation , statistics , combinatorics , image segmentation , physics , image (mathematics) , quantum mechanics , biology , genetics , radiative transfer
Given an arbitrary mesh, we present a method to construct a progressive mesh (PM) such that all meshes in the PM sequence share a common texture parametrization. Our method considers two important goals simultaneously. It minimizes texture stretch (small texture distances mapped onto large surface distances) to balance sampling rates over all locations and directions on the surface. It also minimizes texture deviation (“slippage” error based on parametric correspondence) to obtain accurate textured mesh approximations. The method begins by partitioning the mesh into charts using planarity and compactness heuristics. It creates a stretch-minimizing parametrization within each chart, and resizes the charts based on the resulting stretch. Next, it simplifies the mesh while respecting the chart boundaries. The parametrization is re-optimized to reduce both stretch and deviation over the whole PM sequence. Finally, the charts are packed into a texture atlas. We demonstrate using such atlases to sample color and normal maps over several models.

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