### Abstract

In this paper we propose three simple, but significant improvements to the OoCS (Out-of-Core Simplification) algorithm of Lindstrom which increase the quality of approximations and extend the applicability of the algorithm to an even larger class of compute systems. The original OoCS algorithm has memory complexity that depends on the size of the output mesh, but no dependency on the size of the input mesh. That is, it can be used to simplify meshes of arbitrarily large size, but the complexity of the output mesh is limited by the amount of memory available. Our first contribution is a version of OoCS that removes the dependency of having enough memory to hold (even) the simplified mesh. With our new algorithm, the whole process is made essentially independent of the available memory on the host computer. Our new technique uses disk instead of main memory, but it is carefully designed to avoid costly random accesses. Our two other contributions improve the quality of the approximations generated by OoCS. We propose a scheme for preserving surface boundaries which does not use connectivity information, and a scheme for constraining the position of the "representative vertex" of a grid cell to an optimal position inside the cell.

Original language | English (US) |
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Title of host publication | Proceedings of the IEEE Visualization Conference |

Editors | T. Ertl, K. Joy, A. Varshney |

Pages | 121-126 |

Number of pages | 6 |

State | Published - 2001 |

Event | Visualization 2001 - San Diego, CA, United States Duration: Oct 21 2001 → Oct 26 2001 |

### Other

Other | Visualization 2001 |
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Country | United States |

City | San Diego, CA |

Period | 10/21/01 → 10/26/01 |

### Fingerprint

### Keywords

- External sorting
- Large data
- Out-of-core algorithms
- Polygonal surface simplification
- Quadric error metrics

### ASJC Scopus subject areas

- Computer Science(all)
- Engineering(all)

### Cite this

*Proceedings of the IEEE Visualization Conference*(pp. 121-126)

**A memory insensitive technique for large model simplification.** / Lindstrom, P.; Silva, C. T.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the IEEE Visualization Conference.*pp. 121-126, Visualization 2001, San Diego, CA, United States, 10/21/01.

}

TY - GEN

T1 - A memory insensitive technique for large model simplification

AU - Lindstrom, P.

AU - Silva, C. T.

PY - 2001

Y1 - 2001

N2 - In this paper we propose three simple, but significant improvements to the OoCS (Out-of-Core Simplification) algorithm of Lindstrom which increase the quality of approximations and extend the applicability of the algorithm to an even larger class of compute systems. The original OoCS algorithm has memory complexity that depends on the size of the output mesh, but no dependency on the size of the input mesh. That is, it can be used to simplify meshes of arbitrarily large size, but the complexity of the output mesh is limited by the amount of memory available. Our first contribution is a version of OoCS that removes the dependency of having enough memory to hold (even) the simplified mesh. With our new algorithm, the whole process is made essentially independent of the available memory on the host computer. Our new technique uses disk instead of main memory, but it is carefully designed to avoid costly random accesses. Our two other contributions improve the quality of the approximations generated by OoCS. We propose a scheme for preserving surface boundaries which does not use connectivity information, and a scheme for constraining the position of the "representative vertex" of a grid cell to an optimal position inside the cell.

AB - In this paper we propose three simple, but significant improvements to the OoCS (Out-of-Core Simplification) algorithm of Lindstrom which increase the quality of approximations and extend the applicability of the algorithm to an even larger class of compute systems. The original OoCS algorithm has memory complexity that depends on the size of the output mesh, but no dependency on the size of the input mesh. That is, it can be used to simplify meshes of arbitrarily large size, but the complexity of the output mesh is limited by the amount of memory available. Our first contribution is a version of OoCS that removes the dependency of having enough memory to hold (even) the simplified mesh. With our new algorithm, the whole process is made essentially independent of the available memory on the host computer. Our new technique uses disk instead of main memory, but it is carefully designed to avoid costly random accesses. Our two other contributions improve the quality of the approximations generated by OoCS. We propose a scheme for preserving surface boundaries which does not use connectivity information, and a scheme for constraining the position of the "representative vertex" of a grid cell to an optimal position inside the cell.

KW - External sorting

KW - Large data

KW - Out-of-core algorithms

KW - Polygonal surface simplification

KW - Quadric error metrics

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UR - http://www.scopus.com/inward/citedby.url?scp=0035162683&partnerID=8YFLogxK

M3 - Conference contribution

SP - 121

EP - 126

BT - Proceedings of the IEEE Visualization Conference

A2 - Ertl, T.

A2 - Joy, K.

A2 - Varshney, A.

ER -