SciVisFall2008/Schedule

8/26: Introduction to visualization

Lecturer: Claudio

Topics: Scientific Visualization

Notes: lec01-notes.pdf

Slides: intro

Animations: NCSA storm animation

Further reading:

(Optional reading) Provenance for Computational Tasks: A Survey

8/28: The visualization pipeline

Lecturer: Claudio

Topics: Procedural vs. Dataflow programming; Using Dataflow for the Vis Pipeline; Dataflow programming with VTK; Dataflow programming with VisTrails; python.

Notes: lec02-notes.pdf

Slides: lec02.pdf

Further reading:

(Optional reading) Provenance for Visualizations: Reproducibility and Beyond, C. Silva, J. Freire, and S. Callahan, IEEE Computing in Science and Engineering, 2008.

9/2: Modeling Data for Visualization

Lecturer: Claudio

Topics: Discrete vs continous data; Sampling and interpolation; Point vs triangulated data; Meshing data types; Regular vs irregular data; Tabular data; Vector and tensor fields

Notes: modeling data

Slides: processing.ppt

Further reading:

Basic Signal Processing

Surface Simplification Using Quadric Error Metrics

(Optional Reading) A Memory Insensitive Technique for Large Model Simplification

(Optional Reading) Quadric-based Simplification in any Dimension

9/4: Modeling Data for Visualization

Lecturer: Claudio

Topics: Geometry Processing: Reconstruction and meshing; Simplification; Smoothing; Other Filtering algorithms

Notes: modeling data

Slides: processing.ppt

Further reading:

http://en.wikipedia.org/wiki/Least_squares

(Optional Reading) Robust Moving Least-squares Fitting with Sharp Features

(Optional Reading) Optimal Bandwidth Selection for MLS Surfaces

9/9: Elementary Plotting Techniques

Lecturer: Claudio

Topics: Principles of Graph Construction

Notes: PlottingNotes.pdf

Slides: Plotting1.pdf

Further Reading: There is no required reading for this lecture. For those interested in more depth, the following books are very useful:

• The Elements of Graphing Data. William S. Cleveland, Hobart Press, 2nd Edition, 1994.

• Visualizing Data. William S. Cleveland, Hobart Press, 1993.

• The Visual Display of Quantitative Information. Edward R. Tufte, Graphics Press, 2001.

• Visual Explanations: Images and Quantities, Evidence and Narrative. Edward R. Tufte, Graphics Press, 2997.

9/11: Elementary Plotting Techniques

Lecturer: Claudio

Topics: Simple Plotting Methods: Dot Plots, Connected Symbol Plots, Scatter Plots, Histograms, Others. Advanced Plotting Methods: Multimodal, Higher Dimensional, Correlation, Uncertainty and Variation.

Notes: PlottingNotes.pdf

Slides: Plotting2.pdf

Vistrails: PlottingVistrails.zip - Unzip this file in the examples directory of your VisTrails installation and it will add the vistrails along with their data sets (in the data directory). If you don't have permission to write to this directory (CADE users), then unzip the file where you want. Just be aware that in this case the paths for the data files may not be correct for most vistrails and will need to be fixed before they will execute properly.

Further Reading: There is no required reading for this lecture. Some articles of interest:

• Histogram Bin Size
• Correlation
• Linear Regression
• Box Plots

9/16: Color and Human Perception

Lecturer: Claudio

Topics: Human vision system; Optical illusions

Slides: human-vision.pdf

Links:

http://en.wikipedia.org/wiki/Eye

http://www.grand-illusions.com/gregory2.htm (also, see the related book: [1])

http://en.wikipedia.org/wiki/Purkinje_effect

http://www.handprint.com/HP/WCL/color2.html

9/18: Color and Human Perception

Lecturer: Jens Krueger

Topics: Color Science; Color spaces; Color Blindness; Color maps; Tone mapping;

Slides: colorvision-jens.pdf

Links:

Further reading:

How Not to Lie with Visualization

http://en.wikipedia.org/wiki/Opponent_process

http://en.wikipedia.org/wiki/Color_models

http://en.wikipedia.org/wiki/Absolute_color_space

http://en.wikipedia.org/wiki/Additive_color

http://en.wikipedia.org/wiki/Subtractive_color

http://en.wikipedia.org/wiki/RGB_color_model

http://en.wikipedia.org/wiki/SRGB_color_space

http://en.wikipedia.org/wiki/CIE_XYZ_color_space

9/23: Math refresher

Lecturer: Carlos Scheidegger

Topics: Basic linear algebra; vectors; basic differential geometry (space curves, tangents, normals, surfaces); basic vector calculus (gradient, divergence, curl, gauss' theorem, green's theorem)

Links:

Vector Field Applet

Further Reading:

http://en.wikipedia.org/wiki/Vector_calculus

Appendix A of these notes might be useful: [2]

Two books that take a very accessible approach at vector calculus:

Div, Grad, Curl, and All That: An Informal Text on Vector Calculus

A Student's Guide to Maxwell's Equations

9/25 2D Visualization Techniques

Lecturer: Claudio

Topics: 2-D contours, marching quads, marching tris; Color mapping; height fields; NPR

Slides: pdf file

Notes: pdf file

Vistrails: zip file with ozone.vt and data asymptotic decider in 2d heightfields

Note: These vistrails use relative file paths so you don't need to change each of them individually to match your directory structure. Simply unzip the file to whichever location is more convenient. Then, inside VisTrails, open the VisTrails shell, type:

import os
os.chdir("c:/directory/where/you/unzipped/it")

This will change the directory so you should be able to just run the pipelines.

Further reading:

http://ieeexplore.ieee.org/iel5/4271943/4271944/04272091.pdf

http://www.jstor.org/stable/pdfplus/2683294.pdf

An Efficient Naturalness-Preserving Image-Recoloring Method for Dichromats

9/30: 2D Visualization Techniques

Lecturer: Jens Krueger and Claudio

Topics: 2-D vector fields, div, grad, curl in 2D; Steady vs Unsteady flows; Glyphs; 2-D streamlines, streaklines, pathlines

Slides: pdf file

Further reading:

http://en.wikipedia.org/wiki/Streamlines,_streaklines_and_pathlines

http://en.wikipedia.org/wiki/Euler's_method

http://en.wikipedia.org/wiki/Runge-Kutta

Demos:

http://www.win.tue.nl/~vanwijk/ibfv/

http://www.javaview.de/demo/PaLIC.html

Vistrails: vistrail with steady vector field vis and data vistrail with unsteady vector field vis and data Note: Because VTK does not support time-varying datasets directly, we had to create a reasonably ugly hack to simulate unsteady fields. This means the datasets are quite big (80MB in total).

"The Dx9 Particle Engine" as well as a few datasets

10/2: Volume Vis

Lecturer: Claudio

Topics: Slicing; Contours; Marching algorithms

10/7: Volume Vis

Lecturer: Carlos Scheidegger

Topics: Accelerating structures; High-quality contours

10/9: Volume Vis

Lecturer: Carlos Scheidegger

Topics: High quality isosurfaces

10/21: Direct Volume Rendering

Lecturer: SUB

Topics: Introduction to volume rendering

10/28: Direct Volume Rendering

Lecturer: Claudio

Topics: Structured grid techniques: ray-casting, splatting, texture slicing, shear-warp

11/4: Simplification Techniques

Lecturer: Claudio

Topics: Simplification techniques: vertex clustering, vertex decimation, iterative contraction, quadric error based surface and tetrahedral simplification

11/6: Direct Volume Rendering

Lecturer: Claudio

Topics: Unstructured grid techniques

11/11: Direct Volume Rendering

Lecturer: Claudio

Topics: Transfer function specification

11/13: Tensor Visualization

Lecturer: Claudio

Topics: DT/MRI intro, glyphs, colormapping, volume rendering

11/15: 3D Vector Vis and Topology

Lecturer: Claudio

Topics: 3D techniques, critical points

11/18: Information Visualization

Lecturer: Claudio

Topics: Parallel coordinates; Graph visualization

11/20: Information Visualization

Lecturer: Claudio

Topics: Trees and Graphs; InfoVis Examples

12/2: Aesthetic Issues in Vis

Lecturer: Claudio

Topics: Tufte principles

12/4: Aesthetic Issues in Vis

Lecturer: Claudio

Topics: NPR and Illustrative techniques for Vis