Scientific Visualization

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Scientific Visualization

• CS4550 http//www.gvu.gatech.edu/jarek/lectures/
  
• Jarek Rossignac
• GVC areas
• What is Scientific Visualization
• Course objectives
• Syllabus
• Text book
• Grading

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Jarek (Y-ah-r-eh-ck) Rossignac (Rossignol
cognac)http//www.gvu.gatech.edu/jarek

• Maitrise M.E. Diplome dEngenieur ENSEM (Nancy,
  France)
• PhD E.E. in Solid Modeling (U. of Rochester, NY)
• IBM TJ Watson Research Center (11 years)
• Senior manger Visualization, Modeling, Graphics,
  VR
• Visualization Managed IBM Data Explorer (DX)
  product RD
• Simplification 3D Interaction Acceleration
  (3DIX), OpenGL Accelerator
• Geometry compression VRLM, MPEG-4, awards (ACM
  TOG)
• Georgia Institute of Technology (since 1996)
• Professor, College of Computing, School of
  Interactive Computing
• Director of GVU Center, 1996-2001
• Compression Edgebreaker, Awards (IEEE TVCG)
• Collaborations Sweeps (Korea), IsoSurfaces
  (Spain), Shape Features (Italy), Surgery planning
  (Emory)

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Geometric and Visual Computing areas

• Computer Aided Geometric Design (CAGD)
  Curves/surfaces
• Solid Modeling Representations and Algorithms
  for solids
• Computational Geometry Provably efficient
  algorithms
• Computer-Aided Design (CAD) Automation of Shape
  Design
• Reverse Engineering Fitting surfaces to scanned
  3D points
• Computer-Aided Manufacturing (CAM) NC Machining
• Finite Element Meshing (FEM) Construction and
  simulation
• Animation Capture, Design, Simulation of shape
  behavior
• Visualization Graphical interpretations of
  (large) nD datasets
• Rendering Making (realistic) pictures of 3D
  geometric shapes
• Image-Based Rendering (IBR) Mix images and
  geometry
• Computer Vision Reconstruction of 3D models from
  images
• Virtual Reality (VR) Immersion in interactive
  environments
• Augmented Reality (AR) Track and mark-up what
  you see

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What is Scientific Visualization

• Modeling Represent shapes in a computer
• Rendering Make (realistic) pictures of shapes
  combined with textures, reflectance properties,
  lighting conditions
• Visualization Display information so as to
  reveal relevant meaning/correlation
• Scientific Data is situated (in space and/or
  time) and often represents scalar or vector
  fields (measured or computed)
• Scientific Visualization Analyze these
  scientific data fields, map their properties into
  shapes and photometric attributes, and render
  them in a way that reveals important
  characteristics
• Pushes boundaries of modeling and rendering
  (GPU)

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Course objectives

• Master tools (math, alg, hardware) for Sci Vis
• Expand algorithmic problem-solving abilities
• Practice communication and teamwork skills
• Learn how to find/read publications in the field
• Develop a taste for research
• Have some fun

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Syllabus

• Intro Processing, plotting, exaggeration.
  Project 1 compare plots
• Perception Acuity, Color, Contrast, Optical
  illusions, Curvature, Motion
• Terrains Terrain rendering and editing. Project
  2 compare terrains
• Depiction Surface, Color-coding, Iscocurves,
  Isoclines, Gradient, Silhouettes
• Comparison Discrepancy, Average, Exaggeration,
  Animation, Registration
• Filtering Noise reduction, Smoothing,
  Exaggeration, Local shape analysis
• SegmentationThresholding, Histograms, Snakes,
  Level-sets, Pearling
• Volvis Volume visualization, Translucency,
  Hardware assist
• Exploration View control, Fly-through,
  Cross-sections, Cut-out, Peeling
• Isosurfaces Local Extraction, Consistency,
  Tracing, Crust
• Flow Vector fields, Flow visualization
• Animation IsoSurfaces, Flow, Vibrations
• Tetrahedra Tetrahedra, Representation,
  Simplification, Compression
• Multiresolution Subsample, Simplify, Refine
• Transmission Quantise, Predict, Entropy codecs,
  Streaming, Visibility order
• nD Time-varying volumes, Higher-dimensional
  fields, Parallel coordinates,

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Text books

• Main
• Schroeder, Martin, and Lorensen, The
  Visualization Toolkit - An Object-Oriented
  Approach To 3D Graphics, 4th edition, 520 pages,
  ISBN 1-930934-07-6, Kitware, Inc. publishers.
• Engel et al., Real-time Volume Graphics, Course
  Notes 28, ACM SIGGRAPH 2004
• Additional
• Hansen and Johnson, The Visualization Handbook,
  ISBN 0-12-387582-x, 984 pages, Elsevier, 2004.
• Nielson, Mueler, and Hagen, Scientific
  Visualization Overviews, Methodologies, and
  Techniques, 577 pages, IEEE Press, 1997.

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Grading

• 40 Projects (code and reports) extra credit
  opportunities
• 50 for implementation
• Documented source code
• Running implementation that meets the specs
• Elegance (conciseness) of the implementation
• Extra points Additions, Extensions, Improvements
• 50 for presentation
• Web page with detailed (yet concise)
  explanations,
• Answers to theoretical and algorithmic questions,
  
• Clarity of text, figures, videos
• Choice of test cases illustrating the
  functionality
• References and links to material used for
  inspiration
• Extra points Research questions and ideas, Links
  to useful sites
• 15 Quizzes (in class, closed books)
• 15 Midterm (in class, closed books, 1 page
  cheat-sheet)
• 30 Final (in class, closed books, 1 page
  cheat-sheet)
• Covers whole course, readings, and projects