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Local Prediction Models for Spatiotemporal Volume Visualization
IEEE Transactions on Visualization and Computer Graphics, 2019We present a machine learning-based approach for detecting and visualizing complex behavior in spatiotemporal volumes. For this, we train models to predict future data values at a given position based on the past values in its neighborhood, capturing ...
Gleb Tkachev, S. Frey, T. Ertl
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A Declarative Grammar of Flexible Volume Visualization Pipelines
IEEE Transactions on Visualization and Computer Graphics, 2019This paper presents a declarative grammar for conveniently and effectively specifying advanced volume visualizations. Existing methods for creating volume visualizations either lack the flexibility to specify sophisticated visualizations or are difficult
Min Shih, Charles Rozhon, K. Ma
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Tetrahedra Based Volume Visualization
1998Volume Visualization techniques have advanced considerably since the first international symposium held on this topic eight years ago. This paper brie y reviews the techniques proposed for the visualization of irregular (or scattered) volume datasets.
Cignoni P, Montani C, Scopigno R
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StyleRF-VolVis: Style Transfer of Neural Radiance Fields for Expressive Volume Visualization
IEEE Transactions on Visualization and Computer GraphicsIn volume visualization, visualization synthesis has attracted much attention due to its ability to generate novel visualizations without following the conventional rendering pipeline.
Kaiyuan Tang, Chaoli Wang
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Voxel volumes volume-oriented visualization system
Proceedings Shape Modeling International '99. International Conference on Shape Modeling and Applications, 1999High-speed and effective algorithm of volume rendering is proposed. New methods of object representation by using unified freeforms and arbitrary algebraic surfaces are suggested as well. Proposed algorithm allows to lower complexity of computations, memory and bandwidth requirements in comparison with known methods.
Sergei I. Vyatkin +4 more
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Visualization of the High Surface-to-Volume Ratio of Nanomaterials and Its Consequences
Journal of Chemical EducationWhen bulk materials are reduced in size to the nanometer scale, in particular, their surface-to-volume ratio increases drastically. We introduce some simple experiments on how to visualize this concept to students in the framework of a laboratory class ...
Maria Pozzi +9 more
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Direct Visualization of Deformation in Volumes
Computer Graphics Forum, 2009AbstractDeformation is a topic of interest in many disciplines. In particular in medical research, deformations of surfaces and even entire volumetric structures are of interest. Clear visualization of such deformations can lead to important insight into growth processes and progression of disease.We present new techniques for direct focus+context ...
Stef Busking +2 more
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Research issues in volume visualization
IEEE Computer Graphics and Applications, 1994Volume visualization is a method of extracting meaningful information from volumetric data sets through the use of interactive graphics and imaging. It addresses the representation, manipulation, and rendering of volumetric data sets, providing mechanisms for peering into structures and understanding their complexity and dynamics.
Arie E. Kaufman +4 more
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1991
Three-dimensional volume visualization is a method that allows one to observe and manipulate 3D volumetric data. Many objects and natural phenomena in our spatial and temporal surroundings and in computational models are 3D volumes of data. Unlike traditional techniques, which represent 3D objects in terms of surfaces and edges approximated by polygons
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Three-dimensional volume visualization is a method that allows one to observe and manipulate 3D volumetric data. Many objects and natural phenomena in our spatial and temporal surroundings and in computational models are 3D volumes of data. Unlike traditional techniques, which represent 3D objects in terms of surfaces and edges approximated by polygons
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Statistically Quantitative Volume Visualization
VIS 05. IEEE Visualization, 2005., 2006Visualization users are increasingly in need of techniques for assessing quantitative uncertainty and error in the images produced. Statistical segmentation algorithms compute these quantitative results, yet volume rendering tools typically produce only qualitative imagery via transfer function-based classification.
Joe Michael Kniss +5 more
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