CADIP Information Visualization Work: SFA

1. CADIP Information Visualization Work: SFA • David S. Ebert • Computer Science & Electrical Engineering Department • University of Maryland Baltimore County • ebert@.umbc.edu • Christopher D. Shaw • Computer Science Department • University of Regina • cdshaw@acm.org

2. Talk Outline • Background • Visualization Goals and Challenges • SFA Overview • Procedural Shape Visualization • Results • Recent Work with SFA • New Features • Interactive Lens Visualization • Future Directions

3. Background & Introduction • Visualization • Transforms the abstract and symbolic into the geometric • Harnesses the human perception system (visual?) • Glyph-based Volume Rendering • Advantages of volume rendering • Encodes multidimensional and multivariate information

4. Visualization Goal & Strategy • Goal: • Effectively convey information to the user • Increase the quantity and clarity of the information • Display only as much information as is perceptually understandable • Strategy: • Use perceptual cues to aid understanding of multidimensional and multivariate data

5. Interface Goal & Strategy • Want 3D User Interfaces that are as easy to use as the WIMP style • Use 3D Input devices • Exploit 3D perception with animation & interaction • Enable fine manipulation • Avoid user pain and fatigue

6. Challenge • Rate of Information Increase Greater than Screen Resolution Increase • Rapid increase in number of information sources • Bandwidth of sources increasing • Dimensionality increasing

7. Solutions • More Effective Visualization Techniques • Effective Use of Human Perception • Utilize visual perception characteristics • Add shading cues & stereopsis to increase pre-attentive 3D perception • Utilize proprioception - body’s innate sense of its position in space

8. Utilized in Near Term Visual 3D Spatialization Volume / Size Color Shape (curvature) Opacity Texture Haptic Experimental Proprioception Auditory Olfactory Ergonomics Issues Pain & Fatigue Perceptive Senses Available

9. Our Glyph-based Visualization System: SFA • Minimally-Immersive VR Interface • Multidimensional & Multivariate Data Visualization • Utilizes Many Perceptual Cues

10. SFA System Features • Glyph Rendering • Data dimensions mapped to glyph attributes • Two-handed Interaction • Stereo Viewing • Multivariate, Multidimensional Time-varying Data • Regular and Irregular Grids

11. Rendering Within SFA • Visualizable Parameters: • Location (3) • Color (1-3?) • Transparency (1) • Size (1-3) • Shape (1-14) • Surface Detail (1)

12. Perceptual Cues Used • Shape / Texture • Spatialization • Color • Volume / Size • Proprioception • Stereopsis

13. Minimally-ImmersiveUser Interface - Fishtank VR • Access to environment • Collaboration possible • Low cost (< $10K) • Stereo viewing • Two-handed interaction: • 3-space trackers with buttons • Each hand has a distinct role • Left hand sets up context • Right hand performs fine manipulation

14. Takes Advantage of Proprioceptive Sense “Hold” Volume in 1 Hand, Operate on it with Other Hands Form a Kinematic Chain (Guiard): Left hand is base link, right hand operates relative to it Left is low frequency, Right is high frequency Left Hand Position and orientation of volume Selection of drawing context from 3D hierarchical menu Right Hand Volume subsetting Probe data volume Interactive lens visualization Two-Handed Minimal Immersion

15. Scientific Visualization Results • Application: • Solar Magnetohydrodynamics Simulations • Performance: • 2000+ glyphs at interactive rates on an Indigo2 High Impact

16. Information Visualization • Visualize High Dimensional Abstract Data Spaces • Examples: • Document similarities (50,000+ dimensions) • Database query routing, retrieval of meta-data • Financial data • Document Corpus Management • Information analysis, not just retrieval • Goals: identify trends; find anomalies, themes

17. Results • Visualization of Wall Street Journal Corpus SFA Results IVEE Results

18. Shape Visualization • Utilizing Pre-attentive Ability to Understand Shape (Parker et al.) • Shapes Shouldn’t Detract from Spatialization • Intuitive Shape Mappings (curvature)

19. Parameterized Procedural Shape Visualization • Automatic Generation of Shapes for Data Visualization • Map Data Range to the Parameter Range • Easy • Supports continuous data ranges • Parameterization generates a visual order • May be very slow to generate shapes

20. Parameterized Procedural Shape Visualization • Exploring Three Approaches: • Fractal Detail • Vary surface roughness from smooth to mountainous • Data value determines amount of fractal perturbation to the surface • Superellipsoids • Implicit Surfaces

21. Superquadrics - Superellipsoids • Introduced to Graphics by Barr in 1981 • Extends Quadric Surfaces • With two exponents that control the overall “roundness” or “pointiness” of the shape.

22. Superellipsoids

23. Perception of Superellipsoid Shapes • Just Noticeable Difference Experiment Completed (Chris Shaw) • Both Exponents Changed Together • Result: 21 Superellipsoid Shapes Perceivable

24. Scientific Visualization -Solar Wind MHD Simulation • Opacity = j vorticity • Shape = j velocity -1 • convex = positive velocity • diamonds = zero j velocity • concave = negative velocity

25. Scientific Visualization II • Shape, color, opacity mapped to j vorticity Shape, color, opacity mapped to j vorticity

26. Information Visualization • X =Gold • Y =US $ • Z =Federal Reserve • Shape = Stock Prices • Color =Noriega

27. Implicit Shape Visualization (Rohrer, Ebert, Sibert) • Implicit Surface Modeling (ISM) • Blobby models, metaballs, soft objects • Arbitrarily shaped functions • Automatic blending, CSG • Procedurally-generated • Global Density Field (F) • Produced from sum of potential field source functions F(p) =  fi dist(p)

28. Implicit Shape Visualization Techniques • 1. Document Content • Shape (blobby text) • 2. Corpus Relationships • Proximity clustering • 3. Combine • Content (shape) • Relationships (cluster shells) • Focus+context

29. n Document Visualization: Blobby Text • Map n Dimensions to Equally-spaced Spherical Directions in 3-space • n directions emanating from origin of sphere • Magnitude of directional vectors proportional to corresponding data value • Point source field function at end of vectors

32. New Examples

33. Transparency Textured Implicits

34. Corpus Visualization • Compute Document Similarities • Relationship graph • 3D Proximity Clustering • Mass-spring simulation • Visualization • Fit implicit surface model to cluster space

35. Combined Visualization • 3D Proximity Clustering • Semi-transparent cluster shells • Individual Documents • Content-based shape • Focus+Context • Examples: • InfoViz and Shakespeare’s Richard II and Richard III

37. New Features Multi-vector / glyph display added (3 data dimensions mapped to each vector direction) Multiple dataset display added Data filtering for each data dimension Communication with Fanatic Telltale Communication with Jackal agent completed Standard 2HI techniques now overloaded on mouse interface (subsetting, scale, rotation, zoom) Only 2HI feature not available in mouse interface is the Slice View Substantial documentation Interactive lens visualization Multi-threaded interaction Recent Work with SFA

38. Interactive Lens Visualization Techniques • Three Types: • Contour plate • Texture-based volume rendering • X-ray projection (thin slab) • Allows Display of More Data Variables / Dimensions • To Appear at IEEE Visualization ‘99

39. Contour Plate of Wall Street Journal

40. “X-Ray” Plate of WSJ Data

41. SFA Initial Perceptual Studies • Perceptual Study Experiment Completed this Summer • Initial Results: • 10 steps in transparency • 21 in superquadric shape • Preattentive test -- “Where’s Waldo?” • Experiment Completed, analysis under way

42. Multi-Threaded Interaction: Software Architectures • The usual drawing process is: • Draw on BackRGB while FrontRGB refreshes CRT • Clear BackRGB frame buffer and Z-buffer • Draw all objects in BackRGB+Z • Swap Back and Front RGB buffers • Front buffer is used to refresh CRT • All graphical objects updated simultaneously • Many polygons to draw implies a slow update rate

43. Drawing with 3D Trackers • Usual Process: • Get 3D Tracker position & orientation • Process button hits and interaction with 3D scene • Draw 3D scene • Draw 3D cursors • Swap Buffers • MR Toolkit • Written by Shaw & Green at U of Alberta • Licensed by 600 academic & research sites worldwide

44. 3D Interaction • For True Interaction, Need • >10 updates/second • Lags < 100ms • Lag -- Still the Most Significant Problem • Lags > 50ms are noticeable • Lags >100ms start to affect performance • Lags >500ms destroy interaction • Users adopt move-and-wait strategy

45. Fast Update • How to Get Update Rates > 10 Updates/sec? • Buy a fast graphics computer • Separate application from graphics • SGI Performer uses a 3-stage pipeline • MR Toolkit “Computation” process • Decoupled simulation • Draw less stuff • Decimate polygonal model • Draw cheap approximations • Textures approximate object, perhaps

46. Lag • Lag Is the Time From User Input to Graphics Response • Sum of Lags in System • Tracker lag • Data transmission lag • Drawing lag • How to Get Low Lags? • Predictive filters • Tuning tracker data timing • Fast update rate

47. Multi-Threaded Drawing • Another Solution Class: • Draw in multiple frame buffer segments simultaneously • Draw 3D Cursors on Overlay Planes • Perform 3D interaction in real time • Draw “Full 3D” Scene in RGB + Z Planes • Allow different update rates on the screen • Same advantage as mouse cursor + menus on a 2D frame buffer

48. Video • Video Shows: • SFA with multi-threaded 3D trackers

49. Multi-Thread Advantages • Allows Real-time Update of 3D Tracker Cursors • Overlay update can do menu interaction • Interaction with syntactic elements • RGB update can take as long as it likes • Limited semantic update is possible • picking on the front-buffer data set • Both RGB and Overlay threads are separate from any “Computation” process or thread

50. Create More Java-based Tools (e.g., Alpha, Colormap Editors) Continue to Develop Version That Communicates With Current Agency Tools Finish Time-sequence Support Experiment with Performance of Java-based Glyph Visualization Add Isosurface Rendering for Cluster and Metadata Display Explore Metadata Visualization Techniques and Visualization of LSI Results Extend Perceptual Studies to User Studies of SFA Plans