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Introduction to Visualization and
Advanced Computer Graphics
Jian Huang, CS 594, Spring, 2002
Visualization
• “A picture is worth more than a thousand
words”. – a Chinese proverb
• “A picture is worth more than a thousand
numbers”.
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......
Terrain geometry: (10,20,21), (12,13,14), (13,32,12),....,
(1,2,3), (2,4,5),(3,5,6),.....
Terrain Texture: (23,34,54), (23,34,23), (45,26,78),....
Time 0:
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),...,
Time 1:
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),...
What Is Visualization?
• “seeing is believing”
• we observe and draw conclusions
• seeing is also understanding
• beware of „illusions‟ (magicians)
What Is Visualization?
• Transformation of data or
information into pictures
• engages primary human sensory
apparatus - vision
What Is Visualization?
• Is a Tool for:
– Aid For Learning/Understanding
– Compact Representation Of Information
(e.g. Numbers)
– “Carrier” of Information
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
History
• 1137 - earliest known map (China)
• 1603 - first star charts by Johann
Beyer
• 1637 - cartesian coordinate system
(Descartes)
History (2) - Statistical
• 1686 - first meteorological chart
(Halley)
• 1693 - mortality
tables of city of
Breslau (Halley)
-> first attempt
to correlate two
variables
History (3) - 2D
• Approx. 1750 - contour lines (height)
• 1817 - isotherms (temperature)
• 1829 - isochromatic lines (color)
• 1864 - isobars (pressure)
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
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
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)
History (7) - Augmented Reality.
• 1983 - responsive environments
(Myron Krueger)
• 1995(?) - Cave
Visualization Domains
Volumetric data sources are usually produced by:
• Scanning devices
• Computation (mathematical), or
• Simple measuring
Applications - Vis. As a Toolkit
Application tools usually coupled with
• Haptic feedback devices
• Stereo output (glasses)
• Interactivity
demanding of the rendering algorithm
Scanning - Domains
• Medical scanners (MRI, CT, SPECT, PET,
ultrasound)
Scanning - Applications
• Primary education
• Medical education for surgery, anesthesia
• Illustration of medical procedures to the patient
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?
Scanning (2)
• Domain - biological scanners, electronic
microscopes, confocal microscopes
• Apps - paleontology, microscopic analysis
Scientific Computation - Domain
• Mathematical analysis
• ODE/PDE (ordinary and partial differential
equations)
• Finite element analysis (FE),
• Supercomputer simulations,
Scientific Computation - Apps
• Computational fluid dynamics (CFD),
• Computational field simulations (CFS),
Vector Field Viz Applications
Computational Fluid Dynamics Weather modeling
Vector Field Visualization Challenges
General Goal: Display the field’s directional information
Domain Specific: Detect certain features
Vortex cores, Swirl
Streamlines
A curves that connect all the particle positions
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
Measuring - Domains
• Orbiting satellites
• Spacecraft
• Seismic devices
• Statistical Data
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 …)
Taxonomy
Volumes
Surfaces
Data sampling MRI, Scanners,
CT, Ultrasound
scanning sensors,
Seismic
cameras
visualization
Geometric
model
Image
processing
Image
Supercomputers
(signal) Numerical Simulations
Video
Display
Recording
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
Relation To Other Fields
Illumination
Signal/Image
Engineering
Processing
Optics
Vision Computational
Geometry
Visualization
Applied Psychology
Mathematics Cognition
Hardware User
Interfaces
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
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
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.
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
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
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