Fiber Surfaces: Generalizing Isosurfaces to Bivariate Data

Scientific visualization has many effective methods for examining and exploring scalar and vector fields, but rather fewer for bivariate fields. We report the first general purpose approach for the interactive extraction of geometric separating surfaces in bivariate fields. This method is based on f...

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Veröffentlicht in:Computer graphics forum Jg. 34; H. 3; S. 241 - 250
Hauptverfasser: Carr, Hamish, Geng, Zhao, Tierny, Julien, Chattopadhyay, Amit, Knoll, Aaron
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Blackwell Publishing Ltd 01.06.2015
Wiley
Schlagworte:
Categories and Subject Descriptors (according to ACM CCS)
Computer graphics
Computer Science
Construction
Extraction
Fibers
I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling-Curve
I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling—Curve, surface, solid and object representations
Interactive
Mathematical analysis
Multivariate analysis
Quantitative analysis
Rendering
Scalars
solid and object representations
Studies
surface
Visualization
ISSN:0167-7055, 1467-8659
Online-Zugang:Volltext
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Zusammenfassung:Scientific visualization has many effective methods for examining and exploring scalar and vector fields, but rather fewer for bivariate fields. We report the first general purpose approach for the interactive extraction of geometric separating surfaces in bivariate fields. This method is based on fiber surfaces: surfaces constructed from sets of fibers, the multivariate analogues of isolines. We show simple methods for fiber surface definition and extraction. In particular, we show a simple and efficient fiber surface extraction algorithm based on Marching Cubes. We also show how to construct fiber surfaces interactively with geometric primitives in the range of the function. We then extend this to build user interfaces that generate parameterized families of fiber surfaces with respect to arbitrary polygons. In the special case of isovalue‐gradient plots, fiber surfaces capture features geometrically for quantitative analysis that have previously only been analysed visually and qualitatively using multi‐dimensional transfer functions in volume rendering. We also demonstrate fiber surface extraction on a variety of bivariate data.
Bibliographie:istex:F6296F42A1666591CFD7108453C6BB2A001B1985
ark:/67375/WNG-0XDDBL48-2
ArticleID:CGF12636
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12636