1. Introduction to Visualization and Advanced Computer Graphics Jian Huang, CS 594, Spring, 2002

2. Visualization “A picture is worth more than a thousand words”. – a Chinese proverb “A picture is worth more than a thousand numbers”.

3. It looks like a swirl. There are smaller swirls at the edges. It has different shades of red at the outside, and is mostly green at the inside. The smaller swirls have purple highlights. The green has also different shades. Each small swirl is composed of even smaller ones. The swirls go clockwise. Inside the object, there are also red highlights. Those have different shades of red also. The green shades vary in a fan, while the purple ones are more uni-color. The green shades get darker towards the outside of the fan......

4. (10,20,21), (12,13,14), (13,32,12),...., (1,2,3), (2,4,5),(3,5,6),..... Terrain geometry: Terrain Texture: Time 0: (23,34,54), (23,34,23), (45,26,78),.... Volumetric cloud cover: 0, 0, 12, 14, 15, 15, 17, 12, 23, 45,..... Wind vectors: (0.2, 0.3, 0.93,5), (0.4,0.5,0.76,12),..., Volumetric cloud cover: 0, 0, 11, 12, 13, 16, 20, 12, 32, 45,..... Wind vectors: (0.4,0.5,0.76,12),(0.5,0.5,0.7,6),... Time 1:

5. What Is Visualization? “seeing is believing” we observe and draw conclusions seeing is also understanding beware of ‘illusions’ (magicians)

6. What Is Visualization? Transformation of data or information into pictures engages primary human sensory apparatus - vision

7. What Is Visualization? Is a Tool for: –Aid For Learning/Understanding –Compact Representation Of Information (e.g. Numbers) –“Carrier” of Information

8. Visualization Flavors? Scientific Vis. - User Interfaces, data representation/processing Algorithms, Visual Representations Data Visualization - Include financial data and statistical methods Information Visualization - Abstract Data: WWW documents, file structures, arbitrary relationships

9. History 1137 - earliest known map (China) 1603 - first star charts by Johann Beyer 1637 - cartesian coordinate system (Descartes)

10. History (2) - Statistical 1686 - first meteorological chart (Halley) 1693 - mortality tables of city of Breslau (Halley) -> first attempt to correlate two variables

11. History (3) - 2D Approx. 1750 - contour lines (height) 1817 - isotherms (temperature) 1829 - isochromatic lines (color) 1864 - isobars (pressure)

12. History (4) - 3D Imaging 1895 - X rays by W. Röntgen 1898 - stereo X rays (mackenzie- davidson) - locating foreign bodies in humans 1938 - x-ray sections or slices (3D!) 1912 - x-ray crystallography (Laue) - position of atoms in a crystal

13. History (5) - Computer Graphics 1949 - SAGE air defense - tracked position of aircraft by radar, analyzed results and display on CRT 1965 - sketchpad (Sutherland) - interactive graphical drawing system Used to be BIG and EXPENSIVE

14. History (6) - Scientific Visualiz. 1987 - NSF report [McCormick87] Personal/exploratory graphics - to enable a scientist to gain more knowledge (interact with data) Peer graphics - enable scientist to show information to their colleagues and to collaborate Presentation graphics - communicate information and results (high quality, fully annotated) Publication of visualization - enable others to use the data (replicable)

15. History (7) - Augmented Reality. 1983 - responsive environments (Myron Krueger) 1995(?) - Cave

16. Visualization Domains Volumetric data sources are usually produced by: Scanning devices Computation (mathematical), or Simple measuring

17. Applications - Vis. As a Toolkit Application tools usually coupled with Haptic feedback devices Stereo output (glasses) Interactivity demanding of the rendering algorithm

18. Scanning - Domains Medical scanners (MRI, CT, SPECT, PET, ultrasound)

19. Scanning - Applications Primary education Medical education for surgery, anesthesia Illustration of medical procedures to the patient

20. Scanning - Applications Surgical simulation for treatment planning Tele-medicine Inter-operative visualization in brain surgery, biopsies, etc. Industrial purposes (quality control, security) Games with realistic 3D effects?

21. Scanning (2) Domain - biological scanners, electronic microscopes, confocal microscopes Apps - paleontology, microscopic analysis

22. Scientific Computation - Domain Mathematical analysis ODE/PDE (ordinary and partial differential equations) Finite element analysis (FE), Supercomputer simulations,

23. Scientific Computation - Apps Computational fluid dynamics (CFD), Computational field simulations (CFS),

24. Vector Field Viz Applications Computational Fluid DynamicsWeather modeling

25. Vector Field Visualization Challenges General Goal: Display the field’s directional information Domain Specific: Detect certain features Vortex cores, Swirl

26. Streamlines A curves that connect all the particle positions

27. Streamlines (cont’d) - Displaying streamlines is a local technique because you can only visualize the flow directions initiated from one or a few particles - When the number of streamlines is increased, the scene becomes cluttered - You need to know where to drop the particle seeds - Streamline computation is expensive

28. Measuring - Domains Orbiting satellites Spacecraft Seismic devices Statistical Data

29. Measuring - Applications for military intelligence, weather and atmospheric studies planetary and interplanetary exploration oil, precious metal exploitation, and earth quake studies Statistical Analysis - Info Vis (Financial Data …)

30. Taxonomy Volumes CT, MRI, Ultrasound Seismic Numerical Simulations Surfaces Data Geometric model Voxelization discretization Surface extraction polygonalization Scanners, sensors, cameras sampling scanning Supercomputers Computation / Simulation Image (signal) visualization Image processing Computer vision / Pattern Recognition Computer graphics Display Video Recording

31. Viz vs. Graphics vs.. Imaging Imaging - Enhance, analyze, manipulate and store 2D/3D images Graphics - Make pictures! Digital Image Synthesis: sampling + illumination Visualization - Exploration, transformation, viewing data as images

32. Relation To Other Fields Visualization Vision Signal/Image Processing Illumination Engineering Optics Computational Geometry Applied Mathematics Hardware User Interfaces Psychology Cognition

33. Our Topics Data representation on various types of grids Rendering of scalar and multi-modal data sets Rendering of vector fields and diffusion data sets Efficient iso-surfacing algorithms Distance fields and voxelization Parallel graphics and visualization Point-based graphics Image-based graphics Information visualization Basic geometrical modeling concepts

34. What I expect? Good programming skills in C/C++ Can perform a decent quality design Can think mathematically Basic understanding of parallel or distributed computation Can work independently and would like to do innovative work (a technical report by end of semester) Professional critique and presentation of research work A little sleep deprivation

35. Pre-requisite Understand: viewing pipeline, transformation and rasterization, visibility algorithms, lighting and shading, texture mapping and anti-aliasing Have TA help sessions on these topics.

36. I will not Teach C/C++ Go over every nutty detail of material Teach data structure and algorithm analysis Teach computer architecture Teach parallel programming

37. Publication Opportunities IEEE Conference on Visualization (03/29/2002) IEEE Symposium on Volume Graphics (03/31/2002) IEEE Symposium on Information Visualization (03/29/2002) Eurographics Workshop on Parallel Graphics and Visualization (around 04/15/2002) IEEE Transactions on Visualization and Computer Graphics ACM Transactions on Graphics Many more coming up in later 2002