This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Object-Oriented Visualization
May 1995 (vol. 15 no. 3)
pp. 54-62
Visualization is the process of converting a large set of numbers produced by a numerical simulation or experiment into a graphical image. Since the ultimate goal is to better understand the underlying science, it is crucial to isolate, identify, and quantify important regions and structures. We discuss feature-based techniques which can be incorporated into standard visualization algorithms to greatly enhance the quantification and visualization of observed phenomena.

1. I. Carlbom, I. Chakravarty, and W. Hsu, “Integrating Computer Graphics, Computer Vision, and Image Processing in Scientific Applications,” Computer Graphics (Siggraph 91 Workshop Report), Vol. 26, No. 1, Jan. 1992, pp. 8-16.
2. B. Jahne, Digital Image Processing, Springer Verlag, Berlin, 1991.
3. J.L. Helman and L. Hesselink, "Visualization of Vector Field Topology in Fluid Flows," IEEE Computer Graphics and Applications, vol. 11, no. 3, pp. 36-46, 1991.
4. D. Silver and N. Zabusky, “Quantifying Visualizations for Reduced Modeling in Nonlinear Science: Extracting Structures from Data Sets,” J. Visual Comm. and Image Representation, Vol. 4, No. 1, Mar. 1993, pp. 46-61.
5. D.H. Ballard and C.M. Brown, Computer Vision, Prentice Hall, Upper Saddle River, N.J., 1982.
6. J. Miller et al., “Geometrically Deformed Models: A Method for Extracting Closed Geometric Models from Volumes,” Computer Graphics, Vol. 25, No. 4, July 1991, pp. 217-226.
7. K. Ma, M. Cohen, and J. Painter, “Volume Seeds: A Volume Exploration Technique,” J. Visualization and Computer Animation, Vol. 4, No. 2, 1991, pp. 135-140.
8. J.K. Udupa and D. Odhner, “Shell Rendering,” IEEE Computer Graphics and Applications, vol. 13, no. 6, pp. 58-67, 1993.
9. T. Walsum and F. Post, “Selective Visualization of Vector Fields,” Computer Graphics Forum (Proc. Eurographics 94), Vol. 13, Blackwell, Oxford, 1994, pp. 339-347.
10. S. Liou and A. Singh, “High-Resolution 3D Edge Detection for Non-Uniformly Sampled Images,” tech. manuscript, Siemens Corporate Research, Princeton, N.J., 1993.
11. J. Wilhelms and A. Van Gelder, "Octrees for Faster Isosurface Generation," ACM Trans. Graphics, vol. 11, no. 3, July 1992, pp. 201-227.
12. R. Samtaney et al., “Visualizing Features and Tracking Their Evolution,” Computer, Vol. 27, No. 7, July 1994, pp. 20-27.
1. R. Samtaney, Vorticity in Shock-Accelerated Density-Stratified Interfaces: An Analytical and Computational Study, PhD thesis, Rutgers University, Piscataway, N.J., 1993.
2. O.N. Boratav, R.B. Pelz, and N.J. Zabusky, “Reconnection in Orthogonally Interacting Vortex Tubes: Direct Numerical Simulations and Quantifications,” Physics of Fluids A, Vol. 4, No. 3, 1992, pp. 581-605.
3. P. Woodward, “Interactive Scientific Visualization of Fluid Flow,” Computer, Vol. 26, No. 10, Oct. 1993, pp. 13-25.
4. J. Jimenez et al., “The Structure of Intense Vorticity in Isotropic Turbulence,” J. Fluid Mech., Vol. 255, 1993, pp. 65-90.
5. B. Singer and D. Banks, “Vortex Tubes in Turbulent Flows: Identification, Representation, Reconstruction,” Proc. IEEE Visualization 94, CS Press, Los Alamitos, Calif., 1994, pp. 132-139.

Index Terms:
scientific visualization, feature extraction, CFD, amorphous objects, computer vision
Citation:
Deborah Silver, "Object-Oriented Visualization," IEEE Computer Graphics and Applications, vol. 15, no. 3, pp. 54-62, May 1995, doi:10.1109/38.376613
Usage of this product signifies your acceptance of the Terms of Use.