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View interpolation from a single view 1. Render object 2. Convert Z-buffer to range image 3. Re-render from new viewpoint 4. Use depths to resolve overlaps.

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Presentation on theme: "View interpolation from a single view 1. Render object 2. Convert Z-buffer to range image 3. Re-render from new viewpoint 4. Use depths to resolve overlaps."— Presentation transcript:

1 View interpolation from a single view 1. Render object 2. Convert Z-buffer to range image 3. Re-render from new viewpoint 4. Use depths to resolve overlaps Q. How to fill in holes?

2 View interpolation from multiple views 1. Render object from multiple viewpoints 2. Convert Z-buffers to range images 3. Re-render from new viewpoint 4. Use depths to resolve overlaps 5. Use multiple views to fill in holes

3 Problems with view interpolation resampling the range images –block moves + image interpolation (Chen and Williams, 1993) –splatting with space-variant kernels (McMillan and Bishop, 1995) –fine-grain polygon mesh (McMillan et al., 1997) missed objects –interpolate from available pixels –use more views (from Chen and Williams)

4 More problems with view interpolation Obtaining range images is hard! –use synthetic images (Chen and Williams, 1993) –epipolar analysis (McMillan and Bishop, 1995) cylindrical epipolar geometry epipolar geometry

5 2D image-based rendering advantages –low computation compared to classical CG –cost independent of scene complexity –imagery from real or virtual scenes limitations –static scene geometry –fixed lighting –fixed-look-from or look-at point Flythroughs of 3D scenes from pre-acquired 2D images

6 Apple QuickTime VR outward-looking –panoramic views at regularly spaced points inward-looking –views at points on the surface of a sphere

7 A new solution: rebinning old views must stay outside convex hull of the object like rebinning in computed tomography

8 Generalization: light fields Radiance as a function of position and direction in a static scene with fixed illumination For general scenes  5D function L ( x, y, z,  ) In free space  4D function

9 Two-plane parameterization L ( u, v, s, t ) planes in arbitrary position uses projective geometry fast incremental algorithms

10 A light field is an array of images

11 Spherical 4-DOF gantry for acquiring light fields –0.03 degree positioning error (1mm) –0.01 degree aiming error (1 pixel) –can acquire video while in motion

12 Light field video camera

13 Prototype camera array

14 Geometry-based versus image-based rendering modelimages real-time interactive flythrough conceptual worldreal world offline rendering image analysis real-time rendering image-based rendering model construction image acquisition

15 Another view: the geometry-based/image-based rendering continuum enhanced video –panoramic –multiresolution –multiple viewpoints –video + alpha + Z image-based rendering –QTVR –light fields 3D models more knowledge of scene less knowledge of scene


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