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