Post on 22-Dec-2015
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CS591: Introduction
Mengxia Zhu
Fall 2007
Class objective
To study visualization principles, techniques and algorithms which are used for exploring, transforming and viewing data as computer images to gain understanding and insight into the data.
Introduction to basics of parallel computing and MPI for large scale scientific datasets.
Course materials
No textbook required
Lecture notes Posted on
http://www.cs.siu.edu/~mengxia/Teaching.htm
Research papers Distributed/referred in class
Web sources Referenced in lectures
My expectation
Experience in C programming Basic Algebra and calculus Basic understanding of computer graphics
and OpenGL A little deprivation of sleep…
Grading Policy Midterm and final exam Grading items:
Homework: 20% Mid term and final exam: 30% Lab projects: 40% Paper presentation: 10%
Grading Scale: A = 85% or more B = 75% to 84% C = 65% to 74% D = 50% to 64% F = below 50%
Late submission will be punished. Academic dishonesty will be treated seriously
Office Hours
Regular Hours M, W, F: 12:00PM — 12:50PM
Special Hours Any time by appointment
Contact Info Office: Faner 2142 Email: mzhu@cs.siu.edu Phone: (618)453-6057
Computer Graphics for Visualization OpenGL
Drawing geometric objects
Viewing
Interception and Culling
Lighting and Shading
Special topics
Scientific Visualization
Isosurface rendering
Volume renderingSplattingRaycasting
Vector and tensor visualization
What Visualization?Process of making a computer image or
graph for giving an insight on data/informationTransforming abstract, physical
data/information to a form that can be seen Interpreting in visual terms or putting into
visual forms (i.e., into pictures) Cognitive process
Form a mental image of something Internalize an understanding
Visualization Process
Computation:-simulation/modeling
Measured/ScannedData:
-CT, MRI, ultrasound Financial data:-transactions per day
Data
Transform Map Display
Viz vs. Graphics vs.. Imaging
Imaging - Enhance, analyze, manipulate images
Graphics - Make pictures! geometric data is stored in the computer for the purposes of performing calculations and rendering 2D images
Visualization - Exploration, transformation, viewing data as images
Relation To Other Fields
Visualization
Vision
Signal/ImageProcessing
IlluminationEngineeringOptics
ComputationalGeometry
AppliedMathematics
Hardware UserInterfaces
PsychologyCognition
Extends our visionRemoves limits of human vision in space,
time, frequency and complexityCreates images or pictures of things that
otherwise can not be seen See an object’s internal structure (visible man) See things that are far away or slow in
evolution (stars and nebulas) See microscopic world (crystal structure) See things that move very fast (molecular
dynamics)
Why?
Human Inner Organs Visible (voxel) man
Reconstruction of human body from tomographic datasets of dissected real body
www.uke.uni-hamburg.de
Stars and Emission Nebulas
Visualizing Orion Nebula:
Nadeau et al., Computer
Graphs Forum, 20: 27
(2001)
Crystal Structure
MgSiO3 perovskite
An orthorhombic unit cell
Atomic coordination
Types of Visualization Scientific Visualization
Scientific data Information Visualization
abstract data has no inherent spatial structure thus it does not allow for a straightforward mapping to any geometry with arbitrary relationship
Data Visualization A more general term data sources beyond science such as financial,
marketing, or business data Broad enough to encompass both scientific and
information visualization
Scientific Visualization Relates to and represents something
physical or geometric Images of human brainAir flow over a wing
Data come from scientific computing and measurements
Scientific Computing
Real materials simulation/modelingElectronic calculations Atomistic MD (molecular dynamics)
modelingFinite element (continuum) modeling
Solving differential equationsComputational fluid dynamicsTemperature distribution Electromagnetic field
Example: Air Flow over Windshield Air flow
coming from a dashboard vent and striking the windshield of an automobile
http://www-fp.mcs.anl.gov/fl
Measurement: Medical ImagingStandard brain CT image Volume rendered brain image
http://www.gemedicalsystems.com
Ultrasound
Challenges? Scale
Dimensionality
Data types
Presentation
Interactivity
Data Explosion How to make sense out of the datasets
when they become very large
Scientific dataA million-atom simulation: 7 GB/stepSatellite or space station: TB/dayMRI dataset: 2563 = 16 MB/sliceLaser scanning: 2 million points/minute
Dimensionality Three dimension (trivariate data)
We are in 3D worldVolume visualization (mapping 3D data to
2D screen) Multidimension (hypervariate data)
Car attributes: Make, model, year, miles per gallon, cost, no. of cylinders, size, weight
How to display relationships between many variables
Data Types Structured versus unstructured data
Unstructured (irregular) data are less compact and efficient
Preprocessing of data
Scalar, vector and tensor data Density, temperature Data from flow dynamics Stress-strain data
Non-numerical data Ordinal: days of the week Categorical data: names of animals
Presentation Problem Display without ambiguity
Colors, lighting, translucent, animation, texture mapping
Too much data for too little display area (screen)Too many casesToo many variables
Need to highlight particular cases or variables
Interactivity
Visualization is naturally interactive
Real-time interactions, i.e, virtual environments
Show multiple different perspectives on the data