The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Smooth view-dependent level-of-detail control and its application to terrain rendering
Proceedings of the conference on Visualization '98
Out-of-core simplification of large polygonal models
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
A memory insensitive technique for large model simplification
Proceedings of the conference on Visualization '01
Efficient adaptive simplification of massive meshes
Proceedings of the conference on Visualization '01
A multiphase approach to efficient surface simplification
Proceedings of the conference on Visualization '02
XFastMesh: fast view-dependent meshing from external memory
Proceedings of the conference on Visualization '02
Terrain Simplification Simplified: A General Framework for View-Dependent Out-of-Core Visualization
IEEE Transactions on Visualization and Computer Graphics
Out-of-core construction and visualization of multiresolution surfaces
I3D '03 Proceedings of the 2003 symposium on Interactive 3D graphics
Variable Resolution Terrain Surfaces
Proceedings of the 8th Canadian Conference on Computational Geometry
Managing Large Terrain Data Sets with a Multiresolution Structure
DEXA '00 Proceedings of the 11th International Workshop on Database and Expert Systems Applications
Level of Detail for 3D Graphics
Level of Detail for 3D Graphics
FastMesh: Efficient View-Dependent Meshing
PG '01 Proceedings of the 9th Pacific Conference on Computer Graphics and Applications
External Memory Management and Simplification of Huge Meshes
IEEE Transactions on Visualization and Computer Graphics
Selective Refinement Queries for Volume Visualization of Unstructured Tetrahedral Meshes
IEEE Transactions on Visualization and Computer Graphics
Quick-VDR: Out-of-Core View-Dependent Rendering of Gigantic Models
IEEE Transactions on Visualization and Computer Graphics
Foundations of Multidimensional and Metric Data Structures (The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling)
Large Mesh Simplification using Processing Sequences
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
The Half-Edge Tree: A Compact Data Structure for Level-of-Detail Tetrahedral Meshes
SMI '05 Proceedings of the International Conference on Shape Modeling and Applications 2005
A New Seamless Multi-resolution Simplification Method for the Terrain Model
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
A new simplification method for terrain model using discrete particle swarm optimization
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Dynamic hierarchical triangulation of a clustered data stream
Computers & Geosciences
Out-of-core simplification and crack-free LOD volume rendering for irregular grids
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
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Multi-resolution is a useful tool for managing the complexity of huge terrain and geological data sets. Since encoding large data sets may easily exceed main memory capabilities, data structures and algorithms capable of efficiently working in external memory are needed. In our work, we aim at developing an out-of-core multi-resolution model dimension-independent, that can be used for both terrains, represented by Triangulated Irregular Networks(TINs), and 3D data, such as geological data, represented by tetrahedral meshes. We have based our approach on a general multi-resolution model, that we have proposed in our previous work, which supports the extraction of variable-resolution representations. As first step, we have developed, in a prototype simulation system, a large number of clustering techniques for the modifications in a multi-resolution model. Here, we describe such techniques, and analyze and evaluate them experimentally. The result of this investigation has led us to select a specific clustering approach as the basis for an efficient out-of-core data structure.