Thinking outside the “Visualization” Box
Ken Joy
Visualization and Graphics Research Group
Institute for Data Analysis and Visualization
Computer Science Department
University of California, Davis
Institute for Data Analysis and Visualization
People
Thanks to
Ben Gregorski, Chris Co, Serban Porumbescu, KarimMahrous, Janine Bennett, Lok Hwa, IDAV, UC Davis
Mark Duchaineau, Peter Lindstrom, Valerio Pascucci, LLNL
Josh Senecal, LLNL, Davis
Hans Hagen, Kaiserslautern
Bernd Hamann, UC Davis
Note that the name of our organization has changed.
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The Problem
This is a portion of an isosurfacetaken from the final time step of aRichtmeyer-Meshkov instabilityshock-tube simulation.
The simulation was generated ona 2000x2000x2000 grid. Anisosurface of 460 million triangleswas generated by marchingcubes.
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The Problem
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Simplification, Wavelets, Subdivision
We simplified the mesh.
We generated a fine mesh from a simplified base meshusing Catmull-Clark subdivision.
Invented new Catmull-Clark wavelets to preservefeatures.
Lots of publications, …
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Original
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16% of the coefficients
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5% of the coefficients
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1.6% of the coefficients
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Base Mesh
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Patches
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What did we learn?
We worked on this data set for almost two years, and still didn’thave a interactive “renderable” version.
Occlusion problems were killing us!
Features were disappearing!
…and this was only one isovalue!!!
Data size of this one isosurface exceeded the size of the original dataset.
We had to think outside of “Multiresolution Analysis” to find asolution
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What did we do?
Dynamic generation of the isosurface.
Dynamic extraction based upon a 3D longest-edge-bisectiontetrahedral mesh which is refined and coarsened dependingon viewpoint, error, and frame rate.
Algorithm depends on an innovative storage scheme for themultiresolution data, and an occlusion scheme, allowing real-time display of the isosurface.
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Dynamic Generation of Isosurfaces
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Results!
Dynamic Isosurface Generation – Gregorski, et al. –IEEE Visualization 2002
Time-Varying Isosurfaces – Gregorski, et al. – TVCG,2004
Compression and Occlusion – Gregorski, et al. – IEEEVisualization 2004, submitted.
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Lessons?
We learned that we must think “out of the box” tosolve major problems.
Key words:
Large, massive, terascale
Time varying
Interactive, real-time
Time critical
Mathematically sound
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What happens if the texture is too big?
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Dynamic sensor data!
Potentially billions of sensors
Sensors are scattered and may move in time.
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Problems!
Data is scattered.
Data may move in time.
Applications are time-varying and time-critical.
We cannot afford to generate a mesh for each timestep.
Can we develop visualization methods that do notdepend on a fixed mesh?
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“Meshless” Isosurfaces
“Isosplatting”, Co, et al., 2003
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“Meshless” Isosurfaces
“Isosplatting”, Co, et al., 2003
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“Meshless” Isosurfaces
Solves the multi-block isosurface problem
i.e., no cracks.
Co, et al., VisSym 2004
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Lessons?
Many “mesh” problems can be solved by “meshless”techniques.
Instead of one algorithm for each mesh type…
Thinking outside the “mesh”
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Thinking Outside the “Visualization” Box
Perhaps innovation in visualization can best beachieved by “Thinking outside the box”.
In our research, we frequently think “inside”, workingon the little problems that improve the existingalgorithms.
What about “new” algorithms, “new” techniques,“new” approaches?
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Think outside the “Multiresolution” box
Think outside “subdivision,” “wavelets”, “splines”,“mesh simplification,” etc.
"The key to terascale visualization is deciding what tovisualize."
The key is to focus the data exploration, not to showabsolutely everything.
Queries on Scientific Data Sets.
Find those regions of interest to the user.
Carr, Banff 2004 – Volumetric Queries
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Think outside the “Mesh”
Perhaps think “Meshless”
Solves many problems!
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Think outside the “Big Three”
Are there other “fundamental” visualizationalgorithms besides Slicing, Isosurfaces, and VolumeRendering for scalar fields
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Segmentation Techniques
Nielson and Franke, IEEEVisualization 1997
Bonnell, et al., IEEE Visualization2000, TVCG 2003.
Mahrous, et al. TVCG 2004.
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Think outside the “Heuristic”
Edelsbrunner Corollary (Banff, 2004)
Work in the “sunshine!”
Work in the world of theorems. Theorems requiredeeper thinking about the subject and can show waysto get out of the box.
Corollary: Think outside “linear”
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Think outside the “Scalar Field”
Vector Fields
Tensor Fields
DT-MRI – Can we work with the “original” data?
Multi-valued Fields
Distributions at each data point
Air Quality Problems
Radiation Transport Simulations
Distributions at each data point
Vector distribution at each data point
Tensor distribution at each data point
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Think outside “2D”
Three-dimensional time-varying multivalued dataexploration is HARD. Let’s focus our activities there.
What are separatrices in 3-dimensional vector fields?
What are the topological properties of a 3-dimensional tensorfield?
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Think outside “Static”
The problems of the world are not static problems!
Blood flow cannot be stopped during an MRI (on a human, atleast)
Time-varying Data
Time Critical Data
User-controlled visualizations.
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Think outside “SciVis” and “InfoVis”
Isn’t SciVis just InfoVis with spatial location?
Focus + Context in SciVis?
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Think outside the “Pretty Picture”
AARGH!!!
“It looks good this way”
“Pleasing to my eye”
“Color scheme implies nothing!”
I believe that our field should be called “DataExploration”
“Does it convey the correct information?”
“Is it right?” (Mike Kirby)
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Think outside the “GPU”
Programming the GPU is “Research in Programming”
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Think outside the “Academic Problem”
Hitching our research to someone else’s driving{application} and solving those problems on the owners’terms, leads us to richer {visualization} research. (FredBrooks, 1996)
“Visualization is 40 papers per year.” (Banks, Banff 2004)Therefore, since 1990, the visualization field consists ofapproximately 550 papers.
Where are our “clients”? (Lorensen, 2003)
Is visualization a “relevant” field?
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Ken’s Eleven
Think outside the “Multiresolution” box
Think outside the “Mesh”
Think outside the “Big Three”
Think outside the “Heuristic”
Think outside the “Scalar Field”
Think outside “2D”
Think outside “Static”
Think outside “SciVis” and “InfoVis”
Think outside the “Pretty Picture”
Think outside the “GPU”
Think outside the “Academic Problems”
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HELP ME!
Where do we need to think “outside the box”?
What are the “right” questions to ask?
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Thank You
http://graphics.cs.ucdavis.edu/~joy