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Out-of-core build of a topological data structure from polygon soup
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Source ACM Symposium on Solid and Physical Modeling archive
Proceedings of the sixth ACM symposium on Solid modeling and applications table of contents
Ann Arbor, Michigan, United States
Pages: 171 - 182  
Year of Publication: 2001
ISBN:1-58113-366-9
Authors
Sara McMains  Computer Science Department, University of California, Berkeley
Joseph M. Hellerstein  Computer Science Department, University of California, Berkeley
Carlo H. Séquin  Computer Science Department, University of California, Berkeley
Sponsor
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 3,   Downloads (12 Months): 9,   Citation Count: 7
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ABSTRACT

Many solid modeling applications require information not only about the geometry of an object but also about its topology. Most interchange formats do not provide this information, which the application must then derive as it builds its own topological data structure from unordered, “polygon soup” input. For very large data sets, the topological data structure itself can be bigger than core memory, so that a naive algorithm for building it that doesn't take virtual memory access patterns into account can become prohibitively slow due to thrashing. In this paper, we describe a new out-of-core algorithm that can build a topological data structure efficiently from very large data sets, improving performance by two orders of magnitude over a naive approach.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  7
 
 
 
 

Collaborative Colleagues:
Sara McMains: colleagues
Joseph M. Hellerstein: colleagues
Carlo H. Séquin: colleagues

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