Computer graphics & visualization Point-Based Computer Graphics

download Computer graphics & visualization Point-Based Computer Graphics

If you can't read please download the document

  • date post

    25-Dec-2015
  • Category

    Documents

  • view

    234
  • download

    5

Embed Size (px)

Transcript of Computer graphics & visualization Point-Based Computer Graphics

  • Slide 1
  • computer graphics & visualization Point-Based Computer Graphics
  • Slide 2
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Why Points? huge geometry complexity of current CG models overhead introduced by connectivity of polygonal meshes acquisition devices generate point samples digital 3D photography points complement triangles
  • Slide 3
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Polynomials Rigorous mathematical concept Robust evaluation of geometric entities Shape control for smooth shapes Require proper parameterization Discontinuity modeling Topological flexibility
  • Slide 4
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Polynomilas Triangles Piecewise linear approximations Irregular sampling of the surface No parameterization needed (geometry only)
  • Slide 5
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Triangles Simple and efficient representation Hardware pipelines support triangles Advanced geometric processing The widely accepted queen of graphics primitives Sophisticated modeling is difficult (Local) parameterizations still needed Complex LOD management Compression and streaming is highly non-trivial
  • Slide 6
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Triangles Points Piecewise linear functions to Delta distributions Discrete samples of geometry No connectivity or topology most simple Store all attributes per surface sample
  • Slide 7
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Points geometry complexity of current CG models connectivity overhead of polygonal meshes acquisition devices generate point samples points complement triangles holes compression
  • Slide 8
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group AcquisitionRendering RepresentationProcessing & Editing Point Based Graphics Taxonomy
  • Slide 9
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group How can we capture reality?
  • Slide 10
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Acquisition Contact digitizers intensive manual labor Passive methods require texture, Lambertian BRDF Active light imaging systems restrict types of materials in general fuzzy, transparent, and refractive objects are difficult
  • Slide 11
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group First Method, Laser Range Scanner
  • Slide 12
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Basic Idea Laser Detector Laser Detector
  • Slide 13
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Computing the Distance Laser Detector H L O d d a a
  • Slide 14
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Scattering Issues How optically cooperative is marble?
  • Slide 15
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Image based Acquisition
  • Slide 16
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Image based Acquisition Acquisition Stage 2
  • Slide 17
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Image based Acquisition Acquisition Stage 3
  • Slide 18
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group IBA - Process
  • Slide 19
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Visual Hull
  • Slide 20
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Visual Hull the quality of the visual hull geometry is a function of the number of viewpoints / silhouettes the method is unable to capture all concavities image based lighting
  • Slide 21
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Point Based Rendering Surfels (surface element)
  • Slide 22
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Extended Surfels
  • Slide 23
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Rendering Pipeline
  • Slide 24
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Uniform Reconstruction For uniform samples, use signal processing theory Reconstruction by convolution with low-pass (reconstruction) filter Exact reconstruction of band-limited signals using ideal low-pass filters
  • Slide 25
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Non-Uniform Reconstruction Signal processing theory not applicable for nonuniform samples Local weighted average filtering Normalized sum of local reconstruction kernels
  • Slide 26
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Reconstruction 1D in 2D
  • Slide 27
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Reconstruction 2D in 3D
  • Slide 28
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Algorithm for each sample point { shade surface sample; splat = projected reconstruction kernel; rasterize and accumulate splat; } for each output pixel { normalize; }
  • Slide 29
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Results without Normalization with Normalization
  • Slide 30
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Visibility -z-buffering
  • Slide 31
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Implementation Use a three pass algorithm: 1.Draw depth image with a small depth offset away from the viewpoint Perform regular z-buffering (depth tests and updates), no color updates
  • Slide 32
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Second Pass Draw colored splats with additive blending enabled Perform depth tests, but no updates Accumulate Weighted colors of visible splats in the color channels Weights of visible footprint functions in the alpha channel
  • Slide 33
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Third Pass Normalization of the color channels by dividing through the alpha channel Implemented by render to texture drawing a screen filling quad with this texture performing the normalization in the pixel shader
  • Slide 34
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group Efficient Data Structures DuoDecim A Structure for Point Scan Compression and Rendering
  • Slide 35
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group a.d. 1500 created beautiful statues but missed to make them portable David:434 cm Atlas:208 cm Barbuto:248 cm Florence, Galleria dell'Accademia
  • Slide 36
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Graphics and Visualization Group a.d. 1999 Marc Levoy et al. (Stanford University) did a great job scanning the statues but still missed to make them portable David:1.1 GB Atlas:10 GB All in all 32 gigabytes raw data !!! Jens Krger - Computer Graphics and Visualization Group, TU- Mnchen Image courtesy of Marc Levoy
  • Slide 37
  • computer graphics & visualization Image Synthesis WS 07/08 Dr. Jens Krger Computer Gr