Hardware-Assisted Feature Analysis and Visualization of Procedurally Encoded Multifield Volumetric Data

  • Authors:
  • Manfred Weiler;Ralf Botchen;Simon Stegmaier;Thomas Ertl;Jingshu Huang;Yun Jang;David S. Ebert;Kelly P. Gaither

  • Affiliations:
  • University of Stuttgart;University of Stuttgart;University of Stuttgart;University of Stuttgart;Purdue University;Purdue University;Purdue University;University of Texas

  • Venue:
  • IEEE Computer Graphics and Applications
  • Year:
  • 2005

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Abstract

Procedural encoding of scattered and unstructured scalar datasets using radial basis functions (RBFs) is an active area of research with great potential for compactly representing large data sets. This reduced storage requirement lets the compressed data sets completely reside in the local memory of the graphics card, enabling accurate and efficient processing and visualization without data transfer problems. The article presents a new hierarchical technique that effectively encodes data on arbitrary grids including volumetric scalar, vector, and multifield data. Once the RBF representation is transferred to texture memory, GPU-based visualization using particle advection, cutting planes, isosurfaces, and volume rendering can be performed by functional reconstruction of the encoded data in the fragment pipeline. By eliminating the need for storing and processing mesh information, this approach is particularly attractive for large scattered and irregular structured data sets, as well as data sets created by the emerging field of meshless simulation techniques.