External Memory View-Dependent Simplification
(The Best Paper Award, Eurographics 2000)
Jihad El-Sana and Yi-Jen Chiang
Computer Graphics Forum , vol. 19(3), pp. 139--150,
August 2000
(Special Issue for Eurographics)
Abstract:
In this paper, we propose a novel external-memory algorithm to
support view-dependent simplification for datasets much larger than
main memory. In the preprocessing phase, we use a new spanned
sub-meshes simplification technique to build view-dependence trees
I/O-efficiently, which preserves the correct edge collapsing order
and thus assures the run-time image quality. We further process the
resulting view-dependence trees to build the meta-node trees,
which can facilitate the run-time level-of-detail rendering and is
kept in disk . During run-time navigation, we keep in main memory
only the portions of the meta-node trees that are necessary to render
the current level of details, plus some prefetched portions that
are likely to be needed in the near future. The prefetching
prediction takes advantage of the nature of the run-time traversal of
the meta-node trees, and is both simple and accurate. We also employ
the implicit dependencies for preventing incorrect foldovers, as well
as main-memory buffer management and parallel processes scheme to
separate the disk accesses from the navigation operations, all in an
integrated manner. The experiments show that our approach scales well
with respect to the main memory size available, with encouraging
preprocessing and run-time rendering speeds and without sacrificing
the image quality.
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