DocumentCode :
55731
Title :
Grouper: A Compact, Streamable Triangle Mesh Data Structure
Author :
Luffel, Mark ; Gurung, Topraj ; Lindstrom, Peter ; Rossignac, Jarek
Author_Institution :
Graphics, Visualization, & Usability Center (GVU), Georgia Inst. of Technol., Atlanta, GA, USA
Volume :
20
Issue :
1
fYear :
2014
fDate :
Jan. 2014
Firstpage :
84
Lastpage :
98
Abstract :
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 present a linear-time construction algorithm that allows streaming out Grouper meshes using a small memory footprint while preserving the initial ordering of vertices. As a part of 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 triangleâi.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.
Keywords :
computational complexity; data structures; mesh generation; Grouper; NP-hard optimization problem; SQuad representation; adjacent triangles; all-in-one compact file format; linear-time construction algorithm; memory-efficient sequential stream processing; multicore computers; random-access data structure; shared vertex; streamable representation; streamable triangle mesh data structure; Algorithm design and analysis; File formats; Mathematical model; Mesh generation; Random processes; Mesh compression; large meshes; mesh data structures; out-of-core algorithms; random access;
fLanguage :
English
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
Publisher :
ieee
ISSN :
1077-2626
Type :
jour
DOI :
10.1109/TVCG.2013.81
Filename :
6515117
Link To Document :
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