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3D Photorealistic Modeling Process

3D Photorealistic Modeling Process. Different Sensors. Scanners Local coordinate system Cameras Local camera coordinate system GPS Global coordinate system. Coordinate Systems. Individual local scanner coordinates (each scan)

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3D Photorealistic Modeling Process

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  1. 3D Photorealistic Modeling Process

  2. Different Sensors • Scanners • Local coordinate system • Cameras • Local camera coordinate system • GPS • Global coordinate system

  3. Coordinate Systems • Individual local scanner coordinates (each scan) • Object coordinate system (single coordinate system aligning all scans) • Camera coordinate system (each photograph) • Global coordinates

  4. Scanner Coordinate Z • Individual scanner local coordinate • Not necessary to level Y X

  5. Y X Z Camera Coordinate System • Each photograph has its own coordinates • Units: mm or pixel

  6. Putting it together • From individual scan coordinates to object coordinates • From object (or global) coordinates to camera coordinates • From object coordinates to global coordinates

  7. Individual coordinates to object coordinates (1/2) • Traditional survey approaches • Need to level the scanner • set up backsight • Knowing scanner location and backsight angle • transform each point to the object coordinate system, usually global. • Advantage: • easy to set up • one-step from local to global coordinates. • Disadvantage: • problem in generating mesh models.

  8. From individual coordinates to object coordinates (2/2) • Use mesh alignment techniques (Polyworks) • No need to level. • Requires overlap with common features to minimize the distance. Z T = Y sc1 sc2 X

  9. From Object to Camera (1/2) • Two approaches • Polynomial fit (rubber sheeting) • Low accuracy, • No need to know camera intrinsic parameters • Projection transform (pinhole model) • High accuracy

  10. From Object to Camera (2/2) • From object to camera coordinate system (pin hole model) • Perspective projection to convert to image coordinates (uv, pixel, or mm) 6 unknowns assuming known f Nonlinear-needs initial value

  11. Camera Calibration • Correct lens distortion • Radial distortion • Tangential distortion • Calculate f, k1, k2, p2, p2 in the lab for each lens.

  12. Example of the calibration (Canon 17mm) 1 2 • Radial distortion • Tangential distortion • Complete model 3

  13. Example Iteration = 8 Residuals pts51 = -0.0027 -0.0065 pts50 = 0.0045 0.0085 pts2034 = 0.0050 0.0087 pts 2010 = -0.0066 -0.0100 omage:0.08839938218814 phi:1.36816786714242 kappa: 1.45634479894558 X: -0.975 Y: 0.519 Z: -0.013

  14. Bundle Adjustment Adjust the bundle of light rays to fit each photo

  15. Bundle Adjustment (2/2) Photo no : 7735 pt no U V 14 0.003 -0.006 15 0.003 -0.001 204 -0.001 0.004 205 -0.001 0.009 16 0.017 0.005 206 0.000 0.001 207 -0.001 -0.009 208 0.001 0.010 302 -0.006 -0.009 Photo no : 7734 pt no U V 201 -0.000 -0.000 202 0.000 0.003 203 -0.000 -0.006 14 -0.003 0.012 15 0.000 0.001 204 0.001 -0.004 205 0.001 -0.009 302 0.001 0.004 Photo no omega phi kappa X Y Z 7733 3.5147 78.25411 85.03737 -1.031 0.628 0.046 7734 21.026 79.86519 68.09084 0.419 14.735 -1.055

  16. s From Object to Global (1/2) • 7-parameter conformal transformation Where m11 = cos(phi) * cos(kappa); m12 = -cos(phi) * sin(kappa); m13 = sin(phi) m21 = cos(omega) * sin(kappa) + sin(omage) * sin(phi) * cos(kappa); m22 = cos(omage) * cos(kappa) – sin(omega) * sin(phi) * sin(kappa); m23 = -sin(omage) * cos(phi); m31 = sin(omage) * sin(kappa) – cos(omage) * sin(phi) * cos(kappa); m32 = siin(omage) * cos(kappa) + cos(omage) * sin(phi) * sin(kappa); m33 = cos(omage) * cos(phi); and s is scale factor

  17. Transform to Global (2/2) GPS Object Iteration:5 scale : 0.998986 (*****) omega : 0.22279535 phi : -0.04740587 kappa : 1.45393837 X trans: 24.834 Y trans: 11.698 Z trans: 2.142 Pt: 1, X -0.012 Y 0.042 Z 0.010 Pt: 2, X 0.008 Y -0.004 Z -0.012 Pt: 3, X 0.011 Y 0.012 Z 0.004 Pt: 4, X -0.017 Y -0.032 Z -0.007 Pt: 5, X 0.010 Y -0.018 Z 0.006

  18. REDUCTION TO THE ELLIPSOID D h S H N R Earth Radius 6,372,161 m 20,906,000 ft. S = D x R R + h h = N + H • R S = D x R + N + H Earth Center

  19. REDUCTION TO GRID • Sg = S (Geodetic Distance) x k (Grid Scale Factor) • Sg = 1010.366 x 0.99991176 • = 1010.277 meters

  20. REDUCTION TO ELLIPSOID • S = D x [R / (R + h)] • D = 1010.387 meters (Measured Horizontal Distance) • R = 6,372,162 meters (Mean Radius of the Earth) • h = H + N (H = 158 m, N = - 24 m) • = 134 meters (Ellipsoidal Height) • S = 1010.387 [6,372,162 / 6,372,162 + 134] • S = 1010.387 x 0.999978971 • S = 1010.366 meters

  21. COMBINED FACTOR • CF = Ellipsoidal Reduction x Grid Scale Factor (k) • = 0. 0.999978971 x 0.99991176 • = 0.999890733 • CF x D = Sg • 0.999890733 x 1010.387 = 1010.277 meters

  22. Surface Generation • Through merge process in Polyworks • Through fitting through GoCad • Through direct triangulation (Delauney triangulation, TIN)

  23. Surface cleaning (in Polyworks) • The single most time consuming part of entire process (90% of time). • Filling the holes (because of scan shadow) • Correct triangles

  24. Summarize

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