Hardware-Assisted Feature Analysis and Visualization of Procedurally Encoded Multifield Volumetric Data
Issue No. 05 - September/October (2005 vol. 25)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2005.106
Manfred Weiler , University of Stuttgart
Ralf Botchen , University of Stuttgart
Simon Stegmaier , University of Stuttgart
Thomas Ertl , University of Stuttgart
Jingshu Huang , Purdue University
Yun Jang , Purdue University
David S. Ebert , Purdue University
Kelly P. Gaither , University of Texas
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.
procedural encoding, volume rendering, meshless representation, feature detection, radial basis functions, RBF, flow visualization
Y. Jang et al., "Hardware-Assisted Feature Analysis and Visualization of Procedurally Encoded Multifield Volumetric Data," in IEEE Computer Graphics and Applications, vol. 25, no. , pp. 72-81, 2005.