NDLI: Anisotropic volume rendering for extremely dense, thin line data

Content Provider	IEEE Xplore Digital Library
Author	Schussman, G. Ma, K.-L.
Copyright Year	2004
Description	Author affiliation: Stanford Linear Accelerator Center, Menlo Park, CA, USA (Schussman, G.)
Abstract	Many large scale physics-based simulations which take place on PC clusters or supercomputers produce huge amounts of data including vector fields. While these vector data such as electromagnetic fields, fluid flow fields, or particle paths can be represented by lines, the sheer number of the lines overwhelms the memory and computation capability of a high-end PC used for visualization. Further, very dense or intertwined lines, rendered with traditional visualization techniques, can produce unintelligible results with unclear depth relationships between the lines and no sense of global structure. Our approach is to apply a lighting model to the lines and sample them into an anisotropic voxel representation based on spherical harmonics as a preprocessing step. Then we evaluate and render these voxels for a given view using traditional volume rendering. For extremely large line based datasets, conversion to anisotropic voxels reduces the overall storage and rendering for O(n) lines to O(1) with a large constant that is still small enough to allow meaningful visualization of the entire dataset at nearly interactive rates on a single commodity PC.
Starting Page	107
Ending Page	114
File Size	339893
Page Count	8
File Format	PDF
ISBN	0780387880
DOI	10.1109/VISUAL.2004.5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-10-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Anisotropic magnetoresistance Data visualization Computer graphics Surface reconstruction Linear accelerators Vectors Fluid flow Image storage Rendering (computer graphics) Magnetic fields volume rendering anisotropic lighting line data scientific visualization vector field
Content Type	Text
Resource Type	Article

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