research-article

Attribute Blocks: Visualizing Multiple Continuously Defined Attributes

Author:

James R. MillerAuthors Info & Claims

IEEE Computer Graphics and Applications, Volume 27, Issue 3

Pages 57 - 69

https://doi.org/10.1109/MCG.2007.54

Published: 01 May 2007 Publication History

Publisher Site

Abstract

Attribute Blocks is a new tool for visualizing multiple continuously varying attributes across a region of geospace. Most of the explanations and illustrations of the technique in this article employ climatology data sets along with results computed by a simulation driven by the data sets. However neither the method nor its implementation depend in any way on issues unique to climatological applications. The author demonstrates this in part while comparing the use of Attribute Blocks to other techniques on different types of data sets. The author describes the method, compares it to some earlier methods, illustrates several techniques it enables for locating patterns in data, and briefly discusses how its implementation employs the programmable shader facility in OpenGL.

References

[1]

D.C. Cliburn et al., "Design and Evaluation of a Decision Support System in a Water Balance Application," Computers and Graphics, vol. 26, no. 6, Dec. 2002, pp. 931–949.

Crossref

Google Scholar

[2]

M.C.F. de Oliveira and H. Levkowitz, "From Visual Data Exploration to Visual Data Mining: A Survey," IEEE Trans. Visualization and Computer Graphics, vol. 9, no. 3, July–Sept. 2003, pp. 378–394.

Digital Library

Google Scholar

[3]

A. MacEachren, "Visualizing Uncertain Information," Cartographic Perspective, vol. 13, 1992, pp. 10–19.

Crossref

Google Scholar

[4]

C.G. Healey and J.T. Enns, "Large Datasets at a Glance: Combining Textures and Colors in Scientific Visualization," IEEE Trans. Visualization and Computer Graphics, vol. 5, no. 2, Apr.–June 1999, pp. 145–167.

Digital Library

Google Scholar

[5]

R.J. Rost, OpenGL Shading Language, Addison-Wesley, 2006.

Digital Library

Google Scholar

[6]

D.A. Keim et al., "Pixel-Based Visual Data Mining of Geo-spatial Data," Computers and Graphics, vol. 28, no. 3, June 2004, pp. 327–344.

Crossref

Google Scholar

[7]

D.C. Cliburn et al., "Design and Evaluation of a Decision Support System in a Water Balance Application," Computers and Graphics, vol. 26, no. 6, Dec. 2002, pp. 931–949.

Crossref

Google Scholar

[8]

T.A. Slocum et al., Thematic Cartography and Geographic Visualization, 2nd ed., Pearson Prentice Hall, 2005.

Google Scholar

[9]

J. Beddow, "Shape Coding of Multidimensional Data on a Microcomputer Display," Proc. IEEE Conf. Visualization, IEEE CS Press, 1990, pp. 238–246.

Digital Library

Google Scholar

[10]

A.M. MacEachren et al., "Geovisualization for Knowledge Construction and Decision Support," IEEE Computer Graphics and Applications, vol. 24, no. 1, Jan./Feb. 2004, pp. 13–17.

Digital Library

Google Scholar

[11]

J.E. Rogers and R.E. Groop, "Regional Portrayal with Multi-Pattern Color Dot Maps," Cartographica, vol. 18, no. 4, winter 1981, pp. 51–64.

Crossref

Google Scholar

[12]

R.M. Pickett and G.G. Grinstein, "Iconographic Displays for Visualizing Multidimensional Data," Proc. 1988 IEEE Int'l Conf. Systems, Man, and Cybernetics, 1988, pp. 514–519.

Google Scholar

[13]

P.R. Keller and M.M. Keller, Visual Cues: Practical Data Visualization, IEEE CS Press, 1993.

[14]

Cited By

View all

Jo JVernier FDragicevic PFekete J(2019)A Declarative Rendering Model for Multiclass Density MapsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.286514125:1(470-480)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1109/TVCG.2018.2865141
Kim SPost FZara J(2018)Incorporating visualization research in introductory programming courseProceedings of the 39th Annual European Association for Computer Graphics Conference: Education Papers10.5555/3297765.3297768(9-16)Online publication date: 16-Apr-2018
https://dl.acm.org/doi/10.5555/3297765.3297768
Khlebnikov RKainz BSteinberger MStreit MSchmalstieg D(2012)Procedural Texture Synthesis for Zoom-Independent Visualization of Multivariate DataComputer Graphics Forum10.1111/j.1467-8659.2012.03127.x31:3pt4(1355-1364)Online publication date: 1-Jun-2012
https://dl.acm.org/doi/10.1111/j.1467-8659.2012.03127.x

Index Terms

Attribute Blocks: Visualizing Multiple Continuously Defined Attributes
1. Computing methodologies
2. Software and its engineering
  1. Software creation and management

Recommendations

Using GPU Shaders for Visualization, Part 2

This article describes two visualization applications of GPU shaders: line integral convolution (LIC) and terrain bump-mapping. It also comments on the recent (and rapid) changes to OpenGL and what these mean to educators.
Understanding 3D seismic data visualization with C++, OpenGL and GLSL
Abstract
Seismic data visualization in 3D space is a valuable interpretation tool. Several open-source visualization tools are available. However, little explanation is provided about the inner working of visualization process. The current work discusses ...
Highlights
- Low-level structure of seismic visualization explained in detail with code.
- Texture and shader notions are discussed in application to 3D seismic visualization.
- “Hello world” equivalent source code for 3D seismic data ...
A hybrid GPU rasterized and ray traced rendering pipeline for real time rendering of per pixel effects
ICEC'12: Proceedings of the 11th international conference on Entertainment Computing

Rendering in 3D games typically uses rasterization approaches in order to guarantee interactive frame rates, since ray tracing, a superior method for rendering photorealistic images, has greater computational cost. With the advent of massively parallel ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image IEEE Computer Graphics and Applications

IEEE Computer Graphics and Applications Volume 27, Issue 3

May 2007

88 pages

ISSN:0272-1716

Issue’s Table of Contents

Publisher

IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 May 2007

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 26 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Jo JVernier FDragicevic PFekete J(2019)A Declarative Rendering Model for Multiclass Density MapsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.286514125:1(470-480)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1109/TVCG.2018.2865141
Kim SPost FZara J(2018)Incorporating visualization research in introductory programming courseProceedings of the 39th Annual European Association for Computer Graphics Conference: Education Papers10.5555/3297765.3297768(9-16)Online publication date: 16-Apr-2018
https://dl.acm.org/doi/10.5555/3297765.3297768
Khlebnikov RKainz BSteinberger MStreit MSchmalstieg D(2012)Procedural Texture Synthesis for Zoom-Independent Visualization of Multivariate DataComputer Graphics Forum10.1111/j.1467-8659.2012.03127.x31:3pt4(1355-1364)Online publication date: 1-Jun-2012
https://dl.acm.org/doi/10.1111/j.1467-8659.2012.03127.x

Abstract

References

Cited By

Index Terms

Recommendations

Using GPU Shaders for Visualization, Part 2

Understanding 3D seismic data visualization with C++, OpenGL and GLSL

A hybrid GPU rasterized and ray traced rendering pipeline for real time rendering of per pixel effects

Comments

Information

Published In

Publisher

Publication History

Author Tags

Qualifiers

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations