Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Local adaptive mesh refinement for shock hydrodynamics
Journal of Computational Physics
Geometric concepts for geometric design
Geometric concepts for geometric design
Geometry for n-dimensional graphics
Graphics gems IV
Computing the separating surface for segmented data
VIS '97 Proceedings of the 8th conference on Visualization '97
Automatic detection of open and closed separation and attachment lines
Proceedings of the conference on Visualization '98
Wavelets over curvilinear grids
Proceedings of the conference on Visualization '98
C1-interpolation for vector field topology visualization
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Volume-of-fluid interface tracking with smoothed surface stress methods for three-dimensional flows
Journal of Computational Physics
A topology simplification method for 2D vector fields
Proceedings of the conference on Visualization '00
Constructing material interfaces from data sets with volume-fraction information
Proceedings of the conference on Visualization '00
A tetrahedra-based stream surface algorithm
Proceedings of the conference on Visualization '01
Detection and Visualization of Closed Streamlines in Planar Flows
IEEE Transactions on Visualization and Computer Graphics
Topology-Preserving Smoothing of Vector Fields
IEEE Transactions on Visualization and Computer Graphics
Automatic Vortex Core Detection
IEEE Computer Graphics and Applications
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We present a segmentation approach to scientific visualization that combines the definition of higher-level data, the efficient extraction of meaningful derived feature-like data from defined properties, and the effective visual representation of the extracted data. Our framework is aimed at multi-valued time-varying data sets, where, for example, grid vertices might have a multitude of associated scalar, vector and tensor quantities. This "segmentation" approach to massive data set exploration allows the user to focus upon regions, and interactively explore these regions efficiently. The challenge is to generate this segmented data from existing multi-valued data sets, store this data in an efficient scheme, generate the boundaries of each region, and display these boundaries to the user. We present an integrated scheme that allows a common representation for segmentation, allows it to be applied to a number of data types, and allows derived representations to be calculated. We illustrate this framework with examples from scalar-and vector-field visualization.