Advanced Multimedia
description
Transcript of Advanced Multimedia
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Advanced Multimedia
Warping & MorphingTamara Berg
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Reminder
Project updates next week.
Prepare a 10 minute presentation and submit a 4 paragraph summary to [email protected] by midnight Monday, April 22.
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Image Warping
Slides from: Alexei Efros & Steve Seitz
http://www.jeffrey-martin.com
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Image Transformations
image filtering: change range of imageg(x) = T(f(x))
f
x
Tf
x
f
x
Tf
x
image warping: change domain of imageg(x) = f(T(x))
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Image Transformations
T
T
f
f g
g
image filtering: change range of imageg(x) = T(f(x))
image warping: change domain of imageg(x) = f(T(x))
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Parametric (global) warpingExamples of parametric warps:
translation rotation aspect
affineperspective
cylindrical
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Parametric (global) warping
Transformation T is a coordinate-changing machine:p’ = T(p)
What does it mean that T is global?• Is the same for any point p• can be described by just a few numbers (parameters)
Let’s represent T as a matrix: p’ = Mp
T
p = (x,y) p’ = (x’,y’)
yx
yx
M''
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ScalingScaling a coordinate means multiplying each of its components by
a scalarUniform scaling means this scalar is the same for all components:
2
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Non-uniform scaling: different scalars per component:
Scaling
X 2,Y 0.5
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Scaling
Scaling operation:
Or, in matrix form:
byyaxx
''
yx
ba
yx
00
''
scaling matrix SWhat’s inverse of S?
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Scaling
Scaling operation:
Or, in matrix form:
byyaxx
''
yx
ba
yx
00
''
scaling matrix SWhat’s inverse of S?
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2-D Rotation
(x, y)
(x’, y’)
x’ = x cos() - y sin()y’ = x sin() + y cos()
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2-D Rotation
x = r cos (f)y = r sin (f)x’ = r cos (f + )y’ = r sin (f + )
(x, y)
(x’, y’)
f
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2-D Rotation
x = r cos (f)y = r sin (f)x’ = r cos (f + )y’ = r sin (f + )
Trig Identity…x’ = r cos(f) cos() – r sin(f) sin()y’ = r sin(f) cos() + r cos(f) sin()
(x, y)
(x’, y’)
f
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2-D Rotation
x = r cos (f)y = r sin (f)x’ = r cos (f + )y’ = r sin (f + )
Trig Identity…x’ = r cos(f) cos() – r sin(f) sin()y’ = r sin(f) cos() + r cos(f) sin()
Substitute…x’ = x cos() - y sin()y’ = x sin() + y cos()
(x, y)
(x’, y’)
f
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2-D RotationThis is easy to capture in matrix form:
What is the inverse transformation?
yx
yx
cossinsincos
''
R
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2-D RotationThis is easy to capture in matrix form:
What is the inverse transformation?• Rotation by –• For rotation matrices
yx
yx
cossinsincos
''
TRR 1
R
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Identity?
yyxx
''
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Identity?
yyxx
''
yx
yx
1001
''
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Identity?
yyxx
''
yx
yx
1001
''
2D Scale around (0,0)?
ysy
xsx
y
x
*'
*'
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Identity?
yyxx
''
yx
yx
1001
''
2D Scale around (0,0)?
ysy
xsx
y
x
*'
*'
yx
ss
yx
y
x
00
''
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Rotate around (0,0)?
yxyyxx
*cos*sin'*sin*cos'
yx
yx
cossinsincos
''
2D Shear?
yxshyyshxx
y
x
*'*'
yx
shsh
yx
y
x
11
''
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Mirror about Y axis?
yyxx
''
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Mirror about Y axis?
yyxx
''
yx
yx
1001
''
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Mirror about Y axis?
yyxx
''
yx
yx
1001
''
2D Mirror over (0,0)?
yyxx
''
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Mirror about Y axis?
yyxx
''
yx
yx
1001
''
2D Mirror over (0,0)?
yyxx
''
yx
yx
1001
''
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Translation?
y
x
tyytxx
''
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2x2 MatricesWhat types of transformations can be
represented with a 2x2 matrix?
2D Translation?
y
x
tyytxx
''
Only linear 2D transformations can be represented with a 2x2 matrix
NO!
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All 2D Linear Transformations
Linear transformations are combinations of …• Scale,• Rotation,• Shear, and• Mirror
Properties of linear transformations:• Origin maps to origin• Lines map to lines• Parallel lines remain parallel• Ratios are preserved• Closed under composition
yx
dcba
yx
''
yx
lkji
hgfe
dcba
yx''
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Homogeneous CoordinatesQ: How can we represent translation as a 3x3
matrix?
y
x
tyytxx
''
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Homogeneous CoordinatesHomogeneous coordinates
• represent coordinates in 2 dimensions with a 3-vector
1
coords shomogeneou yx
yx
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Homogeneous CoordinatesQ: How can we represent translation as a 3x3
matrix?
y
x
tyytxx
''
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Homogeneous CoordinatesQ: How can we represent translation as a 3x3
matrix?
A: Using the rightmost column:
100
1001
y
x
tt
ranslationT
y
x
tyytxx
''
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TranslationExample of translation
111001001
1''
y
x
y
x
tytx
yx
tt
yx
tx = 2ty = 1
Homogeneous Coordinates
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TranslationExample of translation
111001001
1''
y
x
y
x
tytx
yx
tt
yx
tx = 2ty = 1
Homogeneous Coordinates
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Basic 2D TransformationsBasic 2D transformations as 3x3 matrices
11000cossin0sincos
1''
yx
yx
11001001
1''
yx
tt
yx
y
x
11000101
1''
yx
shsh
yx
y
x
Translate
Rotate Shear
11000000
1''
yx
ss
yx
y
x
Scale
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Matrix CompositionTransformations can be combined by
matrix multiplication
wyx
sysx
tytx
wyx
1000000
1000cossin0sincos
1001001
'''
p’ = T(tx,ty) R() S(sx,sy) p
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Affine Transformations
Affine transformations are combinations of …• Linear transformations, and• Translations
Properties of affine transformations:• Origin does not necessarily map to origin• Lines map to lines• Parallel lines remain parallel• Ratios are preserved• Closed under composition• Models change of basis
wyx
fedcba
wyx
100''
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Projective Transformations
Projective transformations …• Affine transformations, and• Projective warps
Properties of projective transformations:• Origin does not necessarily map to origin• Lines map to lines• Parallel lines do not necessarily remain parallel• Ratios are not preserved• Closed under composition• Models change of basis
wyx
ihgfedcba
wyx
'''
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Recovering Transformations
What if we know f and g and want to recover the transform T?• willing to let user provide correspondences
– How many do we need?
x x’
T(x,y)y y’
f(x,y) g(x’,y’)
?
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Translation: # correspondences?
How many correspondences needed for translation?
x x’
T(x,y)y y’
?
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Translation: # correspondences?
How many correspondences needed for translation?How many Degrees of Freedom?
x x’
T(x,y)y y’
?
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Translation: # correspondences?
How many correspondences needed for translation?How many Degrees of Freedom?What is the transformation matrix?
x x’
T(x,y)y y’
?
100
'10'01
yy
xx
pppp
M
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Euclidian: # correspondences?
How many correspondences needed for translation+rotation?How many DOF?
x x’
T(x,y)y y’
?
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Affine: # correspondences?
How many correspondences needed for affine?How many DOF?
x x’
T(x,y)y y’
?
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Affine: # correspondences?
How many correspondences needed for affine?How many DOF?
x x’
T(x,y)y y’
?
wyx
fedcba
wyx
100''
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Projective: # correspondences?
How many correspondences needed for projective?How many DOF?
x x’
T(x,y)y y’
?
wyx
ihgfedcba
wyx
'''
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Example: warping triangles
Given two triangles: ABC and A’B’C’ in 2D (12 numbers) Need to find transform T to transfer all pixels from one to
the other.How can we compute the transformation matrix:
T(x,y)
?
A
B
C A’C’
B’
Source Destination
11001''
yx
fedcba
yx
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Example: warping triangles
Given two triangles: ABC and A’B’C’ in 2D (12 numbers) Need to find transform T to transfer all pixels from one to
the other.How can we compute the transformation matrix:
T(x,y)
?
A
B
C A’C’
B’
Source Destination
11001''
yx
fedcba
yx cp2transform in matlab!
input – correspondences. output – transformation.
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Image warping
Given a coordinate transform (x’,y’) = T(x,y) and a source image f(x,y), how do we compute a transformed image g(x’,y’) = f(T(x,y))?
x x’
T(x,y)
f(x,y) g(x’,y’)
y y’
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f(x,y) g(x’,y’)
Forward warping
Send each pixel f(x,y) to its corresponding location (x’,y’) = T(x,y) in the second image
x x’
T(x,y)
Q: what if pixel lands “between” two pixels?
y y’
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f(x,y) g(x’,y’)
Forward warping
Send each pixel f(x,y) to its corresponding location (x’,y’) = T(x,y) in the second image
x x’
T(x,y)
Q: what if pixel lands “between” two pixels?
y y’
A: distribute color among neighboring pixels (x’,y’)– Known as “splatting”
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Image warping
Given a coordinate transform (x’,y’) = T(x,y) and a source image f(x,y), how do we compute a transformed image g(x’,y’) = f(T(x,y))?
x x’
T(x,y)
f(x,y) g(x’,y’)
y y’
imtransform in matlab! input – transform and source image output – transformed image.
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Image warping
+
Target Source
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Image warping
+
Target Source
User clicks on 4 points in target, 4 points in source.
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Image warping
+
Target Source
User clicks on 4 points in target, 4 points in source.Find best affine transformation between source subimg and target subimg.
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Image warping
+
Target Source
User clicks on 4 points in target, 4 points in source.Find best affine transformation between source subimg and target subimg.Transform the source subimg accordingly.
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Image warping
+
Target Source
User clicks on 4 points in target, 4 points in source.Find best affine transformation between source subimg and target subimg.Transform the source subimg accordingly.Insert the transformed source subimg into the target image.
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Image warping
+
Target Source
User clicks on 4 points in target, 4 points in source.Find best affine transformation between source subimg and target subimg.Transform the source subimg accordingly.Insert the transformed source subimg into the target image.
Useful matlab functions: ginput, cp2transform, imtransform.
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Image warping
+
Target Source
= Result
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Image warping in video
Do the same thing, but for a bunch of frames in a video!
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Image Morphing - Women in Art video
http://youtube.com/watch?v=nUDIoN-_Hxs
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Morphing = Object Averaging
The aim is to find “an average” between two objects• Not an average of two images of objects…• …but an image of the average object!• How can we make a smooth transition in time?
– Do a “weighted average” over time t
How do we know what the average object looks like?• We haven’t a clue!• But we can often fake something reasonable
– Usually required user/artist input
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Idea #1: Cross-Dissolve
Interpolate whole images:Imagehalfway = (1-t)*Image1 + t*image2
This is called cross-dissolve in film industry
But what if the images are not aligned?
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Idea #2: Align, then cross-disolve
Align first, then cross-dissolve• Alignment using global warp – picture still valid
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Dog Averaging
What to do?• Cross-dissolve doesn’t work• Global alignment doesn’t work
– Cannot be done with a global transformation (e.g. affine)• Any ideas?
Feature matching!• Nose to nose, tail to tail, etc.• This is a local (non-parametric) warp
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Idea #3: Local warp, then cross-dissolve
Morphing procedure: for every t,1. Find the average shape (the “mean dog”)
• local warping2. Find the average color
• Cross-dissolve the warped images
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Warp specification - sparseHow can we specify the warp?
Specify corresponding points• interpolate to a complete warping function• How do we do it?
How do we go from feature points to pixels?
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Triangular Mesh
1. Input correspondences at key feature points
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Triangular Mesh
1. Input correspondences at key feature points2. Define a triangular mesh over the points
• Same mesh in both images!• Now we have triangle-to-triangle correspondences
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Triangular Mesh
1. Input correspondences at key feature points2. Define a triangular mesh over the points
• Same mesh in both images!• Now we have triangle-to-triangle correspondences
3. Warp each triangle separately from source to destination• How do we warp a triangle?• 3 points = affine warp!
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Warp interpolationHow do we create an intermediate warp at time t?
• Assume t = [0,1]• Simple linear interpolation of each feature pair• (1-t)*p1+t*p0 for corresponding features p0 and p1
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Image MorphingWe know how to warp one image into the other, but how
do we create a morphing sequence?1. Create an intermediate shape (by interpolation)2. Warp both images towards it3. Cross-dissolve the colors in the newly warped images
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Morphing & matting
Extract foreground first to avoid artifacts in the background
Slide by Durand and Freeman