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Graphics research and courses at Stanford

Graphics research and courses at Stanford. http://graphics.stanford.edu. Leo Guibas modeling, geometry. Pat Hanrahan rendering, architectures. Marc Levoy sensing, modeling, rendering. Ron Fedkiw simulation, natural phenomena. Chris Bregler animation, motion capture. Graphics faculty.

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Graphics research and courses at Stanford

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  1. Graphics research and courses at Stanford http://graphics.stanford.edu

  2. Leo Guibasmodeling, geometry Pat Hanrahanrendering, architectures Marc Levoysensing,modeling, rendering Ron Fedkiw simulation, natural phenomena Chris Bregler animation, motion capture Graphicsfaculty

  3. Mark HorowitzVLSI, hardware Bill Dallycomputer architecture Terry Winogradhuman-computer interaction Bernd Girod (EE)imaging, video, networking Relatedareas

  4. Digital Michelangelo project Solving the Forma Urbis Romae Visualizing cuneiform tablets Modeling subsurface scattering Multi-image digital photography Measuring and modeling reflectance Acquisition and display of light fields Image-based modeling and rendering Real-time volume rendering Interactive workspaces Parallel graphics architectures Stanford immersive television project Texture analysis-synthesis methods Motion analysis / synthesis Automatic illustration systems Physics-based modeling and simulation Visualization of computer systems Real-time programmable shading Research projects …and many more

  5. Digital Michelangelo project(Levoy) • very large geometric models • scientific tool for art historians • virtual museums, multimedia, replicas • lasting archive of important cultural artifacts

  6. David’s left eye

  7. vision problems aligning and merging scans automatic hole filling inverse color rendering automated view planning digital archiving problems making the data last forever robust 3D digital watermarking indexing and searching 3D data real-time viewing on low-cost PCs Research challenges

  8. The Forma Urbis Romae(Levoy) • 60’ x 45’ x 4” marble map of ancient Rome, carved 200 A.D. • shows the city at a scale where you can see every room • now in 1,163 fragments, an open problem for 500 years

  9. linear features 2D contours 3D surfaces Solving the puzzle • algorithms must be fast • minimize false positives • robust to effects of weathering

  10. Real-Time Programmable Shading(Hanrahan) • high-level languages for programmable graphics hardware • RenderMan in real-time • guide the future of graphics hardware • parallelizing scientific computations on the same hardware

  11. Modeling subsurface scattering(Hanrahan, Levoy) • translucency is caused by multiple scattering • approximated by volumetric diffusion • validation using physical measurements

  12. sensing vision compression transmission decompression graphics Stanford Immersive Television Project(Bregler, Dally, Girod, Hanrahan, Horowitz, Levoy) • light field cameras • real-time range scanning Intel DTV tuner card

  13. Light field cameras(Horowitz, Levoy, Hanrahan) video light field camera spherical light field camera

  14. light stripe object projector camera one pixel over time one frame Real-time range scanning time space

  15. holes can be found and filled on-the-fly • object or scanner can be handheld / shoulderheld video frame range data merged model(159 frames)

  16. Motion analysis / synthesis(Bregler) Acquisition Analysis Animation Kinematics Dynamics Language ?

  17. Physics-based modeling and simulation(Fedkiw) • new computational algorithms for numerical simulation of physical phenomena Water - simulated using the Navier Stokes equations and the level set method for implicit surface evolution. A solid “invisible” sphere initiates the splashing.

  18. Physics-based modeling and simulation(Fedkiw) • new computational algorithms for numerical simulation of physical phenomena Smoke - simulated as a scalar in a flow field generated using the Navier Stokes equations. Photon mapping is used for the visualization.

  19. Virtual Human(oid) Project (Fedkiw) • derive and improve physics-based models of tissues, organs, organ systems, clothing

  20. Kinetic Data Structures(Guibas) • A kinetic data structure(KDS)maintains an attribute of interest in a collection of moving or deforming objects. • Examples include many kinds ofproximity, visibility, or connectivityinformation. • This yields efficient algorithms for collision detection, visibility maintenance, and aggregation orcommunication among mobile nodes.

  21. Interactive workspaces (iRoom)(Winograd, Fox, Hanrahan) • multiple display surfaces • multiple interaction devices • flexible display architecture • facilitates group work The ultra-high resolution Interactive Mural integrates desktop access, sketching, 3D models, and images under pen-based control

  22. Courses • CS 148 – Introductory Computer Graphics • CS 248 – Introduction to Computer Graphics • CS 348A – Mathematical Foundations (modeling) • CS 348B – Image Synthesis Techniques (rendering) • CS 348C – Animation Techniques • CS 338 – Level Set Methods • CS 368 – Geometric algorithms (computational geometry) • CS 448 – Topics in Computer Graphics • CS 468 – Topics in Geometric Algorithms

  23. Examples of topics • CS 448 - Topics in Computer Graphics • experiments in digital television • interactive workplaces • modeling appearance This year: • graphics architectures (Autumn, Hanrahan) • digital photography (Spring, Levoy) • CS 468 - Topics in Geometric Algorithms • matching techniques and similarity measures

  24. Maneesh Agrawala < maneesh@pepper.stanford.edu > Sean Anderson < seander@cs.stanford.edu > Robert Bosch < bosch@cs.stanford.edu > Ian Buck < ianbuck@graphics.stanford.edu > Cindy Chen < xcchen@graphics.stanford.edu > Milton Chen < miltchen@graphics.stanford.edu > Scott Cohen < scohen@cs.stanford.edu > Joao Comba < comba@cs.stanford.edu > James Davis < jedavis@cs.stanford.edu > Matthew Eldridge < eldridge@graphics.stanford.edu > Reid Gershbein < rsg@uni.stanford.edu > Francois Guimbretiere < francois@graphics.stanford.edu > Olaf Hall-Holt < olaf@cs.stanford.edu > David Hoffman < hoffman@cs.stanford.edu > Greg Humphreys < humper@graphics.stanford.edu > Homan Igehy < homan@graphics.stanford.edu > Brad Johanson < bjohanso@stanford.edu > Menelaos Karavelas < menelaos@graphics.stanford.edu > Dave Koller < dk@graphics.stanford.edu > Song Sam Liang < sliang@graphics.stanford.edu > Tamara Munzner < munzner@cs.stanford.edu > Bradley Nelson < bdnelson@stanford.edu > John Owens < jowens@graphics.stanford.edu > Lucas Pereira < lucasp@graphics.stanford.edu > Matt Pharr < mmp@lux.stanford.edu > Kekoa Proudfoot < kekoa@graphics.stanford.edu > Katheline Pullen < pullen@graphics.stanford.edu > Timothy Purcell < tpurcell@graphics.stanford.edu > Ravi Ramamoorthi < ravir@graphics.stanford.edu > Szymon Rusinkiewicz < smr@graphics.stanford.edu > Gordon Stoll < gws@aperture.stanford.edu > Chris Stolte < cstolte@graphics.stanford.edu > Diane Tang < dtang@cs.stanford.edu > Yelena Vileshina < lena@graphics.stanford.edu > Li-Yi Wei < liyiwei@graphics.stanford.edu > PhD students http://graphics.stanford.edu

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