Image-Based Rendering Relief textures - PowerPoint PPT Presentation

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Image-Based Rendering Relief textures

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????????????? ??????????? (??????????) ? ???????? ???????? ?????? ... Draw a little cloud (splat) instead of a pixel in desired image. ... – PowerPoint PPT presentation

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Title: Image-Based Rendering Relief textures


1
?????? ??????????? ?? ????????????.?????????
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2
??????? ?? ??????
  • ???????? ? ?????? ??????????? ?? ????????????
    (Image-Based Rendering)
  • ?????????? ?????? IBR
  • ????????? ???????? (relief textures)

3
Traditional Rendering
  • For photorealism
  • Modeling is hard
  • Rendering is slow

User input texture maps, survey data
Modeling
Geometry Textures Light sources
Rendering
Images
4
Image-Based Rendering
  • ???????? ????
  • ????????????? ??????????? (??????????) ? ????????
    ???????? ??????
  • ????????????? ??????? ????????? ??????????? ???
    ????????????.

5
Image-Based Rendering
  • For photorealism
  • Fast modeling
  • Complexity independent rendering

Images user input range scanners
Modeling
Images depth maps
Rendering
Images
6
Traditional vs. Image-based
  • Image based computer graphics has three main
    advantages
  • Photorealism of produced images
  • The speed
  • Simple modeling

7
Simplest IBR methods. Texture
  • Texture - is the simplest of IBR methods.

8
Simplest IBR methods. Sprites
  • Texture simple planar geometry Sprite
  • Sprites are taken from certain camera position
    (sprite camera)

9
Simplest IBR methods. Sprites
  • No geometry information and...
  • Sprites are looking good from view-points close
    to the sprite camera, but awful from others

10
3D model rendering distortions
  • What are we missing?
  • The effect of 3-dimensionality on the screen is a
    combination of two effects perspective
    distortion and parallax
  • Sprites are capable of producing perspective
    distortions but they are unable to produce
    correct parallax effect

11
Sprites with Depth
  • Combine depth and color
  • Color texel now is a 3D sample.

12
Warping
  • Using the samples z-values, image can be
    transformed (or warped), to enchance the image
    descriptive power (realism)

13
Planar pinhole camera
14
Orthographic camera
15
3D point position from a pinhole camera
  • One image is not enough to determine location of
    a point in 3D.

16
From two cameras
  • If we have two cameras, Camera1 and Camera2 with
    different parameters, capturing the same scene
    from different locations, a point can be
    expressed as

17
Warping example
18
Schematic view
Warping x warp(x)
Depth map
Final view
Parallax, perspective projection, translation
19
Relief textures
  • Most of modern 3D accelerators can ultimately
    fast render textured triangles
  • gt We can use this capability to speed up and
    simplify Image-Based Rendering
  • Such an algorithm is called Relief Textures

20
Schematic view
Software Hardware
Pre-warping
Texture mapping
Relief textures
Final view
Warped textures
Parallax
Perspective projection, translation
21
New warping function
  • x warp(x) g(h(x), Poly),
  • where
  • g(y, Poly) is texture-mapping function and
    usually done in hardware
  • h(x) is pre-warpring function

22
New warping function (2)
  • Prewarping function h(x) after some optimizations
    looks like following
  • u2 (u1mud)nud
  • v2 (v1mvd)nvd
  • Extremely simple, isnt it?

23
Two stage warping example
24
Two stage warping example (2)
25
Filling holes
  • This sprite with depth was warped to the new
    viewpoint
  • Look how many empty spaces on the women face and
    hair at the picture
  • Lets call them holes

26
Two classes of holes
  • All the holes fall into two classes by its nature
  • Resampling problem
  • Missing information

27
Resampling
Before warping
After warping
28
Resampling methods
  • Methods to fill the holes
  • Inverse warping
  • Meshing
  • Splatting
  • Interpolation

29
Splatting
  • Draw a little cloud (splat) instead of a pixel in
    desired image. This cloud has to be opaque in its
    center becoming more and more transparent to its
    sides
  • Features
  • Relatively small computation cost
  • Not all the holes are filled

30
Interpolation
  • Use the fact that u and v are independent from
    each other after pre-warping (two-pass algorithm)
    and linearly interpolate depth and color in the
    intermediate and final images

31
Interpolation (2)
32
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