Selective refinement queries for volume visualization of unstructured tetrahedral meshes
In this paper, we address the problem of the efficient visualization of large irregular volume data sets by exploiting a multiresolution model based on tetrahedral meshes. Multiresolution models, also called Level-Of-Detail (LOD) models, allow encoding the whole data set at a virtually continuous ra...
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1998. - 10(2004), 1 vom: 25. Jan., Seite 29-45 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , |
| Format: | Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2004
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics |
| Schlagworte: | Comparative Study Evaluation Study Journal Article Research Support, Non-U.S. Gov't Validation Study |
| Zusammenfassung: | In this paper, we address the problem of the efficient visualization of large irregular volume data sets by exploiting a multiresolution model based on tetrahedral meshes. Multiresolution models, also called Level-Of-Detail (LOD) models, allow encoding the whole data set at a virtually continuous range of different resolutions. We have identified a set of queries for extracting meshes at variable resolution from a multiresolution model, based on field values, domain location, or opacity of the transfer function. Such queries allow trading off between resolution and speed in visualization. We define a new compact data structure for encoding a multiresolution tetrahedral mesh built through edge collapses to support selective refinement efficiently and show that such a structure has a storage cost from 3 to 5.5 times lower than standard data structures used for tetrahedral meshes. The data structures and variable resolution queries have been implemented together with state-of-the art visualization techniques in a system for the interactive visualization of three-dimensional scalar fields defined on tetrahedral meshes. Experimental results show that selective refinement queries can support interactive visualization of large data sets |
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| Beschreibung: | Date Completed 19.10.2004 Date Revised 10.12.2019 published: Print Citation Status MEDLINE |
| ISSN: | 1077-2626 |