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CNR ExploRA
Conference object . 2005
Data sources: CNR ExploRA
https://doi.org/10.1109/vis.20...
Article . 2006 . Peer-reviewed
Data sources: Crossref
https://doi.org/10.1109/visual...
Article . 2006 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2023
Data sources: DBLP
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Batched Multi Triangulation

Authors: Cignoni P; Ganovelli F; Gobbetti E; Marton F; Ponchio F; Scopigno R;

Batched Multi Triangulation

Abstract

The Multi Triangulation framework (MT) is a very general approach for managing adaptive resolution in triangle meshes. The key idea is arranging mesh fragments at different resolution in a Directed Acyclic Graph (DAG) which encodes the dependencies between fragments, thereby encompassing a wide class of multiresolution approaches that use hierarchies or DAGs with predefined topology. On current architectures, the classic MT is however unfit for real-time rendering, since DAG traversal costs vastly dominate raw rendering costs. In this paper, we redesign the MT framework in a GPU friendly fashion, moving its granularity from triangles to precomputed optimized triangle patches. The patches can be conveniently tri-stripped and stored in secondary memory to be loaded on demand, ready to be sent to the GPU using preferential paths. In this manner, central memory only contains the DAG structure and CPU workload becomes negligible. The major contributions of this work are: a new out-of-core multiresolution framework, that, just like the MT, encompasses a wide class of multiresolution structures; a robust and elegant way to build a well conditioned MT DAG by introducing the concept of V -partitions, that can encompass various state of the art multiresolution algorithms; an efficient multithreaded rendering engine and a general subsystem for the external memory processing and simplification of huge meshes.

Country
Italy
Keywords

I.3.5 Computational Geometry and Object Modeling

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    17
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Average
Top 10%
Top 10%