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Title: Grouper: A Compact, Streamable Triangle Mesh Data Structure

Journal Article · · IEEE Transactions on Visualization and Computer Graphics
DOI:https://doi.org/10.1109/TVCG.2013.81· OSTI ID:1186779
 [1];  [1];  [2];  [1]
  1. Georgia Inst. of Technology, Atlanta, GA (United States). Visualization and Usability Center (GVU)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

Here, we present Grouper: an all-in-one compact file format, random-access data structure, and streamable representation for large triangle meshes. Similarly to the recently published SQuad representation, Grouper represents the geometry and connectivity of a mesh by grouping vertices and triangles into fixed-size records, most of which store two adjacent triangles and a shared vertex. Unlike SQuad, however, Grouper interleaves geometry with connectivity and uses a new connectivity representation to ensure that vertices and triangles can be stored in a coherent order that enables memory-efficient sequential stream processing. We also present a linear-time construction algorithm that allows streaming out Grouper meshes using a small memory footprint while preserving the initial ordering of vertices. In this construction, we show how the problem of assigning vertices and triangles to groups reduces to a well-known NP-hard optimization problem, and present a simple yet effective heuristic solution that performs well in practice. Our array-based Grouper representation also doubles as a triangle mesh data structure that allows direct access to vertices and triangles. Storing only about two integer references per triangle-i.e., less than the three vertex references stored with each triangle in a conventional indexed mesh format-Grouper answers both incidence and adjacency queries in amortized constant time. Our compact representation enables data-parallel processing on multicore computers, instant partitioning and fast transmission for distributed processing, as well as efficient out-of-core access. We demonstrate the versatility and performance benefits of Grouper using a suite of example meshes and processing kernels.

Research Organization:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC52-07NA27344
OSTI ID:
1186779
Report Number(s):
LLNL-JRNL-503653
Journal Information:
IEEE Transactions on Visualization and Computer Graphics, Vol. 20, Issue 1; ISSN 1077-2626
Publisher:
IEEE
Country of Publication:
United States
Language:
English

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