Efficient streamline, streamribbon, and streamtube constructions on unstructured grids

Ueng, Shyh‐Kuang; Sikorski, C.; Ma, Kwan‐Liu

doi:10.1109/2945.506222

Cited by 56 publications

(7 citation statements)

References 11 publications

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“…Given an initial point x in a field, a streamline can be calculated by solving this initialvalue problem. We apply a fourth-order Runge-Kutta scheme, see [15], to integrate the equation stepwise.…”

Section: Clustering and Error Measurementsmentioning

confidence: 99%

Construction of vector field hierarchies

Heckel

Weber

Hamann

et al. 1999

Proceedings Visualization '99 (Cat. No.99CB37067)

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We present a method for the hierarchical representation of vector fields. Our approach is based on iterative refinement using clustering and principal component analysis. The input to our algorithm is a discrete set of points with associated vectors. The algorithm generates a top-down segmentation of the discrete field by splitting clusters of points. We measure the error of the various approximation levels by measuring the discrepancy between streamlines generated by the original discrete field and its approximations based on much smaller discrete data sets. Our method assumes no particular structure of the field, nor does it require any topological connectivity information. It is possible to generate multiresolution representations of vector fields using this approach.

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Section: Clustering and Error Measurementsmentioning

confidence: 99%

Construction of vector field hierarchies

Heckel

Weber

Hamann

et al. 1999

Proceedings Visualization '99 (Cat. No.99CB37067)

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“…A simple linear function can be used for the color mapping from function value range In vector field visualization, the commonly used techniques are streamlines [11] and streamribbons [12]. We make use of streamlines.…”

Section: Error Metric For Multi-valued Volume Datamentioning

confidence: 99%

Adaptive Multi-Valued Volume Data Visualization using Data-Dependent Error Metrics

Gray¹,

Linsen²,

Hamann³

et al. 2005

International Journal of Modelling and Simulation

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Adaptive, and especially view-dependent, volume visualization is used to display large volume data at interactive frame rates preserving high visual quality in specified or implied regions of importance. In typical approaches, the error metrics and refinement oracles used for viewdependent rendering are based on viewing parameters only. The approach presented in this paper considers viewing parameters and parameters for data exploration such as isovalues, velocity field magnitude, gradient magnitude, curl, or divergence. Error metrics are described for scalar fields, vector fields, and more general multi-valued combinations of scalar and vector field data. The number of data being considered in these combinations is not limited by the error metric but the ability to use them to create meaningful visualizations. Our framework supports the application of visualization methods such as isosurface extraction to adaptively refined meshes. For multi-valued data exploration purposes, we combine extracted mapping with color information and/or streamlines mapped onto an isosurface. Such a combined visualization seems advantageous, as scalar and vector field quantities can be combined visually in a highly expressive manner.

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“…Our algorithm has several interesting applications, of which the rendering of streamlines is one of the most important ones. Previously streamlines were mostly rendered with real geometry like streamtubes or -ribbons [15], or as illuminated lines [16].…”

Section: Applicationsmentioning

confidence: 99%

“…Several methods have been introduced to visualize streamlines in the past years. Ueng et al [15] use stream-ribbons and streamtubes to visualize the flow, the first being a quad strip generated by the streamline and a normal vector extracted with it and the second being a generalized cylinder with a circular profile where the radius depends on the flow velocity. No efficient rendering algorithm for the stream-tubes was proposed though.…”

Section: Introductionmentioning

confidence: 99%

Visualization with stylized line primitives

Gumhold

Seidel

IEEE Visualization 2005 - (VIS'05)

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Line primitives are a very powerful visual attribute used for scientific visualization and in particular for 3D vector-field visualization. We extend the basic line primitives with additional visual attributes including color, line width, texture and orientation. To implement the visual attributes we represent the stylized line primitives as generalized cylinders. One important contribution of our work is an efficient rendering algorithm for stylized lines, which is hybrid in the sense that it uses both CPU and GPU based rendering. We improve the depth perception with a shadow algorithm. We present several applications for the visualization with stylized lines among which are the visualizations of 3D vector fields and molecular structures.

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Efficient streamline, streamribbon, and streamtube constructions on unstructured grids

Cited by 56 publications

References 11 publications

Construction of vector field hierarchies

Construction of vector field hierarchies

Adaptive Multi-Valued Volume Data Visualization using Data-Dependent Error Metrics

Visualization with stylized line primitives

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