Introduction to Visualization and Advanced Computer GraphicsVisualizationPowerPoint PresentationSlide 4Slide 5Slide 6Slide 7Slide 8HistoryHistory (2) - StatisticalHistory (3) - 2DHistory (4) - 3D ImagingHistory (5) - Computer GraphicsHistory (6) - Scientific Visualiz.History (7) - Augmented Reality.Visualization DomainsApplications - Vis. As a ToolkitScanning - DomainsScanning - ApplicationsSlide 20Scanning (2)Scientific Computation - DomainScientific Computation - AppsVector Field Viz ApplicationsVector Field Visualization ChallengesStreamlinesStreamlines (cont’d)Slide 28Slide 29TaxonomySlide 31Slide 32Our TopicsWhat I expect?Pre-requisiteI will notPublication OpportunitiesIntroduction to Visualization and Advanced Computer GraphicsJian Huang, CS 594, Spring, 2002Visualization•“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......(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: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 - visionWhat Is Visualization?•Is a Tool for:–Aid For Learning/Understanding–Compact Representation Of Information (e.g. Numbers)–“Carrier” of InformationVisualization 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 relationshipsHistory•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 variablesHistory (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 crystalHistory (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 EXPENSIVEHistory (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(?) - CaveVisualization DomainsVolumetric data sources are usually produced by:•Scanning devices•Computation (mathematical), or•Simple measuringApplications - Vis. As a ToolkitApplication tools usually coupled with•Haptic feedback devices•Stereo output (glasses)•Interactivitydemanding of the rendering algorithmdemanding of the rendering algorithmScanning - Domains•Medical scanners (MRI, CT, SPECT, PET, ultrasound)Scanning - Applications•Primary education•Medical education for surgery, anesthesia •Illustration of medical procedures to the patientScanning - 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 analysisScientific 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 ApplicationsComputational Fluid Dynamics Weather modelingVector Field Visualization ChallengesGeneral Goal: Display the field’s directional informationDomain Specific: Detect certain features Vortex cores, SwirlStreamlinesA curves that connect all the particle positionsStreamlines (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 expensiveMeasuring - Domains•Orbiting satellites•Spacecraft•Seismic devices•Statistical DataMeasuring - 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 …)TaxonomyVolumesCT, MRI, UltrasoundSeismicNumerical SimulationsSurfacesDataGeometricmodelVoxelizationdiscretizationSurface extractionpolygonalizationScanners, sensors,camerassamplingscanningSupercomputersComputation /
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