Name
Abstract | ||
|---|---|---|
Shape modeling is an integral part of many visualization problems. Recent advances in scanning technology and a number of surface reconstruction algorithms have opened up a new paradigm for modeling shapes from samples. Many of the problems currently faced in this modeling paradigm can be traced back to two anomalies in sampling, namely undersampling and oversampling. Boundaries, non-smoothness and small features create undersampling problems, whereas oversampling leads to too many triangles. We use Voronoi cell geometry as a unified guide to detect undersampling and oversampling. We apply these detections in surface reconstruction and model simplification. Guarantees of the algorithms can be proved. In this paper we show the success of the algorithms empirically on a number of interesting data sets. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/VISUAL.2001.964497 | IEEE Visualization 2003 |
Keywords | DocType | ISSN |
computational geometry,data visualisation,image reconstruction,image sampling,rendering (computer graphics),Voronoi cell geometry,computational geometry,data sets,geometric modeling,mesh generation,model simplification,modeling paradigm,non-smoothness,oversampling,polygonal mesh reduction,sample based shape modeling,scanning technology,surface reconstruction,surface reconstruction algorithms,undersampling,visualization problems | Conference | 1070-2385 |
ISBN | Citations | PageRank |
0-7803-7200-X | 7 | 0.90 |
References | Authors | |
28 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tamal K. Dey | 1 | 2349 | 169.82 |
| Joachim Gieseny | 2 | 927 | 68.20 |
| Samrat Goswami | 3 | 447 | 24.77 |
| James Hudson | 4 | 111 | 6.31 |
| Rephael Wenger | 5 | 441 | 43.54 |
| Wulue Zhao | 6 | 194 | 11.75 |