CS1315:
Introduction to
Media Computation
Feature Based Image Morphing
Image Morphing
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Examples
Technique
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This technique is based Beier-Neely feature-based
image metamorphosis paper
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http://www.hammerhead.com/thad/morph.html
Feature Based Morphing
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The idea of feature based morphing is that lines are drawn
over prominent features in each image, e.g. eyes, nose,
mouth, etc.
Over time the lines in the source image are moved
towards the lines in the destination image, which creates
the warping effect on the image
While the lines are moving, the surrounding pixels are
transformed based on the movement
A cross-dissolve, or a type of blending, is performed to
transform the colors of the source image to the colors of
the destination image
Single Line Transformation
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We define a line
from point P’ to
point Q’ in the
source image
We define another
line from point P to
point Q in the
destination image
Single Line Transformation
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For each pixel in the
destination image, we
calculate three values to remap the current pixel in the
source image caused by the
line warping
u is the position along the
from P to Q
v is the perpendicular
distance from the line from P
to Q
X’ is the re-mapped pixel
value
u = (X-P)*(Q-P)
||Q-P||^2
v = (X-P)*Perp(Q-P)
||Q-P||
X’ = P’ + u*(Q’-P’) +
v*Perp(Q’-P’)
||Q’-P’||
Note: * is the dot product
Single Line Transformation
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Example:
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The destination image pixel at (50, 35) is replaced with the
source image pixel at (80, 56)
Multiple Line Transformations
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Generating the warping effect with multiple lines is basically the same
as with a single line, but the u, v, and X’ calculations are performed by
comparing each pixel to each line in the list of lines
Because different lines should effect pixels more or less, depending on
relative location and line length, three new constants are introduced
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a = line strength by proximity
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b = line strength by relative distance
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If a is barely > 0, if line is very close to the pixel, the strength is nearly
infinite. Larger values provide smoother warping, but less preciseness.
Typical Range: [0.5, 2]
If b is 0, all lines contribute equally regardless of distance
p = line strength by weight
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Typical Range: [0, 1]
If p is 0, all lines have same weight, if p is 1 longer lines have greater
weight than shorter lines
Multiple Line Transformations
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These new constants a, b, and p are used to
calculate a weight that is added to the X’ pixel
value to adjust the value according to relative line
strength
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weight = ( length^p / (a + distance) )^b
Add more details here
Morphing Two Images
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The source image lines and destination image lines are
interpolated over time. This provides a gradual transition
from the source image to the destination image
To provide the best looking morph, the source lines and
the destination lines are is warped towards the
interpolated lines. This allows the features to line up for
each frame and generates a more smooth and gradual
morph
As the lines are warped, the images are cross-dissolved to
enhance the transition
Cross-Dissolve
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Add code here
Morphing Movie
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Once all the morphing frames are created and
saved to a new image, the frames can be turned
into a movie
Add movie code calls here