Thursday, September 21

Multi-resolution Tools for Exploring Large Data Sets

2:00 PM-4:00 PM

Multi-resolution simulation methods are used to allocate computational samples in ways that adapt to varying needs across the region of interest. The idea that similar methods can be used during the analysis process is attractive, particularly since hardware available for analysis is typically more modest. However, the factors determining the required resolution are quite different. The limited field of view and finite resolution of display devices constrain what can be seen. Interaction with a large data set causes these display constraints to vary dynamically. The speakers will present current research in multi-resolution methods for data exploration.

Organizer: Samuel P. Uselton
Lawrence Livermore National Laboratory, USA
2:00-2:25 Simplification Methods for Scalar Fields Defined Over Scattered Data Sets
Kenneth I. Joy, University of California at Davis, USA
2:30-2:55 Hierarchical Representations of Triangular and Tetrahedral Meshes
Oliver G. Staadt, Swiss Federal Institute of Technology, ETH-Zurich, Switzerland
3:00-3:25 Geometric Simplifications for Polygonal Models
Amitabh Varshney, University of Maryland at College Park, USA
3:30-3:55 Subdivision-based Multi-resolution Modeling
Denis Zorin, Courant Institute of Mathematical Sciences, New York University, USA

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