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Output-Sensitive 3D Line Integral Convolution
July/August 2008 (vol. 14 no. 4)
pp. 820-834
ASCII Text
x 
 
Martin Falk, Daniel Weiskopf, "Output-Sensitive 3D Line Integral Convolution," IEEE Transactions on Visualization and Computer Graphics, vol. 14, no. 4, pp. 820-834, July/August, 2008.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2008.25,
author = {Martin Falk and Daniel Weiskopf},
title = {Output-Sensitive 3D Line Integral Convolution},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {14},
number = {4},
issn = {1077-2626},
year = {2008},
pages = {820-834},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2008.25},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - Output-Sensitive 3D Line Integral Convolution
IS - 4
SN - 1077-2626
SP820
EP834
EPD - 820-834
A1 - Martin Falk,
A1 - Daniel Weiskopf,
PY - 2008
KW - Three-Dimensional Graphics and Realism
KW - Picture/Image Generation
VL - 14
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
We propose an output-sensitive visualization method for 3D line integral convolution (LIC) whose rendering speed is largely independent of the data set size and mostly governed by the complexity of the output on the image plane. Our approach of view-dependent visualization tightly links the LIC generation with the volume rendering of the LIC result in order to avoid the computation of unnecessary LIC points: early-ray termination and empty-space leaping techniques are used to skip the computation of the LIC integral in a lazy-evaluation approach. Different noise models are discussed, covering dense representations based on filtered white noise all the way to sparse representations similar to oriented LIC. A range of illumination models is applied to the LIC streamlines: different codimension-2 lighting models as well as a novel gradient-based illumination model that relies on precomputed gradients and does not require any direct calculation of gradients after the LIC integral is evaluated. Finally, we demonstrate that our visualization approach lends itself to a fast GPU implementation that supports both steady and unsteady flow. Applications to flow visualization in combination with feature extraction and focus-and-context visualization are described, a comparison to previous methods is provided, and a detailed performance analysis is included.

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Index Terms:
Three-Dimensional Graphics and Realism, Picture/Image Generation
Citation:
Martin Falk, Daniel Weiskopf, "Output-Sensitive 3D Line Integral Convolution," IEEE Transactions on Visualization and Computer Graphics, vol. 14, no. 4, pp. 820-834, July-Aug. 2008, doi:10.1109/TVCG.2008.25
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