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Matting and Transparency

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Title: Matting and Transparency


1
Matting and Transparency
15-463 Computational Photography Alexei Efros,
CMU, Fall 2008
2
How does Superman fly?
  • Super-human powers?
  • OR
  • Image Matting?

3
Physics of Alpha Matting
Semi-transparent objects
Pixels too large
4
alpha channel
  • Add one more channel
  • Image(R,G,B,alpha) Sprite!
  • Encodes transparency (or pixel coverage)
  • Alpha 1 opaque object (complete coverage)
  • Alpha 0 transparent object (no coverage)
  • 0ltAlphalt1 semi-transparent (partial coverage)
  • Example alpha 0.7

Partial coverage or semi-transparency
5
Multiple Alpha Blending
  • So far we assumed that one image (background) is
    opaque.
  • If blending semi-transparent sprites (the A over
    B operation)
  • Icomp aaIa (1-aa)abIb
  • acomp aa (1-aa)ab
  • Note sometimes alpha is premultiplied
    im(aR,aG,aB,a)
  • Icomp Ia (1-aa)Ib
  • (same for alpha!)

6
Pulling a Matte
  • Problem Definition
  • The separation of an image C into
  • A foreground object image Co,
  • a background image Cb,
  • and an alpha matte a
  • Co and a can then be used to composite the
    foreground object into a different image
  • Hard problem
  • Even if alpha is binary, this is hard to do
    automatically (background subtraction problem)
  • For movies/TV, manual segmentation of each frame
    is infeasible
  • Need to make a simplifying assumption

7
Average/Median Image
  • What can we do with this?

8
Background Subtraction
-

9
Crowd Synthesis (with Pooja Nath)
  1. Do background subtraction in each frame
  2. Find and record blobs
  3. For synthesis, randomly sample the blobs, taking
    care not to overlap them

10
Background Subtraction
  • A largely unsolved problem

Estimated background
Difference Image
Thresholded Foreground on blue
One video frame
11
Blue Screen
12
Blue Screen matting
  • Most common form of matting in TV studios
    movies
  • Petros Vlahos invented blue screen matting in the
    50s. His Ultimatte is still the most popular
    equipment. He won an Oscar for lifetime
    achievement.
  • A form of background subtraction
  • Need a known background
  • Compute alpha as SSD(C,Cb) gt threshold
  • Or use Vlahos formula a 1-p1(B-p2G)
  • Hope that foreground object doesnt look like
    background
  • no blue ties!
  • Why blue?
  • Why uniform?

13
The Ultimatte
p1 and p2
14
Blue screen for superman?
15
Semi-transparent mattes
  • What we really want is to obtain a true alpha
    matte, which involves semi-transparency
  • Alpha between 0 and 1

16
Matting Problem Mathematical Definition
17
Why is general matting hard?
18
Solution 1 No Blue!
19
Solution 2 Gray or Flesh
20
Triangulation Matting (Smith Blinn)
  • How many equations?
  • How many unknowns?
  • Does the background need to be constant color?

21
The Algorithm
22
Triangulation Matting Examples
23
More Examples
24
More examples
25
Problems with Matting
  • Images do not look realistic
  • Lack of Refracted Light
  • Lack of Reflected Light

Solution Modify the Matting Equation
26
Environment Matting and Compositing
slides by Jay Hetler Douglas E. Zongker
Dawn M. Werner Brian Curless David H. Salsin
27
Environment Matting Equation
  • C F (1- a)B F
  • C Color
  • F Foreground color
  • B Background color
  • a Amount of light that passes through the
    foreground
  • F Contribution of light from Environment that
    travels through the object

28
Explanation of F
R reflectance image T Texture image
29
Environment Mattes
30
Performance
  • Calibration
  • Matting 10-20 minutes extraction time for each
    texture map (Pentium II 400Mhz)
  • Compositing 4-40 frames per second
  • Real-Time?

31
How much better is Environment Matting?
Alpha Matte Environment Matte
Photograph
32
How much better is Environment Matting?
Alpha Matte Environment Matte
Photograph
33
Movies!
34
Fast Separation of Direct and Global Images
Using High Frequency Illumination
  • Shree K. Nayar
  • Gurunandan G. Krishnan
  • Columbia University

Michael D. Grossberg City College of New York
Ramesh Raskar MERL
SIGGRAPH Conference Boston, July 2006 Support
ONR, NSF, MERL
35
Direct and Global Illumination
surface
source
P
camera
36
Direct and Global Components Interreflections
surface
source
i
camera
37
High Frequency Illumination Pattern
surface
source
camera
38
High Frequency Illumination Pattern
surface
source
camera
fraction of activated source elements
39
Separation from Two Images
direct
global
40
Other Global Effects Subsurface Scattering
translucent surface
source
camera
41
Other Global Effects Volumetric Scattering
participating medium
surface
source
camera
42
(No Transcript)
43
Scene
44
Scene
45
Real World Examples Can You Guess the Images?
46
Eggs Diffuse Interreflections
47
Wooden Blocks Specular Interreflections
48
Kitchen Sink Volumetric Scattering
Volumetric Scattering Chandrasekar 50, Ishimaru
78
49
Peppers Subsurface Scattering
50
Hand
Skin Hanrahan and Krueger 93, Uchida 96, Haro
01, Jensen et al. 01, Cula and Dana 02, Igarashi
et al. 05, Weyrich et al. 05
51
Face Without and With Makeup
Without Makeup
With Makeup
52
Blonde Hair
Hair Scattering Stamm et al. 77, Bustard and
Smith 91, Lu et al. 00 Marschner et al. 03
53
www.cs.columbia.edu/CAVE
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