Histogram spectra for multivariate time-varying volume LOD selection

Level of detail techniques are widely applied to minimize sampling error subject to working set size constraints. Typical large data sets being produced today have many variables sampled across time-varying volumes. Visualization of these multivariate volumes is commonly phrased in terms of conditio...

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Published in:2011 IEEE Symposium on Large Data Analysis and Visualization pp. 39 - 46
Main Authors: Martin, S., Han-Wei Shen
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2011
Subjects:
Context
Data visualization
Equations
Histograms
Level of detail selection
Linear programming
Multivariate volume visualization
Optimization
Rendering (computer graphics)
Time-varying volume visualization
ISBN:9781467301565, 1467301566
Online Access:Get full text
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Abstract Level of detail techniques are widely applied to minimize sampling error subject to working set size constraints. Typical large data sets being produced today have many variables sampled across time-varying volumes. Visualization of these multivariate volumes is commonly phrased in terms of conditional expressions such as "show variable A where variable B is between B 1 and B 2 ." The bounds, B 1 and B 2 , tend to be specified during the interactive portion of the workflow. Thus, to maximize quality over the salient interval, level of detail selection should also be interactive. We introduce the concept of histogram spectra to quickly and compactly quantify the statistical sensitivity of volumes to sampling. Salient interval volumes of one or more variables are used to select which parts of the histogram spectra are important. The level of detail selection problem, over a time-varying, multivariate, multiresolution volume, is then posed as an integer programming problem using the histogram spectra. We propose an efficient solution enabling interactive LOD selection on large, out-of-core volumes and show its efficacy on two real data sets from different problem domains.
AbstractList Level of detail techniques are widely applied to minimize sampling error subject to working set size constraints. Typical large data sets being produced today have many variables sampled across time-varying volumes. Visualization of these multivariate volumes is commonly phrased in terms of conditional expressions such as "show variable A where variable B is between B 1 and B 2 ." The bounds, B 1 and B 2 , tend to be specified during the interactive portion of the workflow. Thus, to maximize quality over the salient interval, level of detail selection should also be interactive. We introduce the concept of histogram spectra to quickly and compactly quantify the statistical sensitivity of volumes to sampling. Salient interval volumes of one or more variables are used to select which parts of the histogram spectra are important. The level of detail selection problem, over a time-varying, multivariate, multiresolution volume, is then posed as an integer programming problem using the histogram spectra. We propose an efficient solution enabling interactive LOD selection on large, out-of-core volumes and show its efficacy on two real data sets from different problem domains.
Author Han-Wei Shen
Martin, S.
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  surname: Han-Wei Shen
  fullname: Han-Wei Shen
  email: hwshen@cse.ohio-state.edu
  organization: Ohio State Univ., Columbus, OH, USA
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Snippet Level of detail techniques are widely applied to minimize sampling error subject to working set size constraints. Typical large data sets being produced today...
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StartPage 39
SubjectTerms Context
Data visualization
Equations
Histograms
Level of detail selection
Linear programming
Multivariate volume visualization
Optimization
Rendering (computer graphics)
Time-varying volume visualization
Title Histogram spectra for multivariate time-varying volume LOD selection
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