Advanced Computer Graphics Spring 2005

1
Advanced Computer Graphics
(Spring 2005)

• COMS 4162, Lecture 6 Image Compositing,
  Morphing
  
• Ravi Ramamoorthi

http//www.cs.columbia.edu/cs4162
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To Do

• Assignment 1, Due Feb 15.
• This week only extra credit and clear up
  difficulties
  
• Questions/difficulties so far in doing
  assignment?
  

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Digital Image Compositing

• 1996 Academy scientific and engineering
  achievement award (oscar ceremony) For their
  pioneering inventions in digital image
  compositing

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Image Compositing

• Separate an image into elements
• Each part is rendered
  
  separately
  
• Then pasted together or
  
  composited into a scene

Many slides courtesy Tom Funkhouser
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Outline

• Compositing or combining images
  Fundamental problem in graphics images from
  different sources, put them together
  
• Blue screen matting
• Alpha channel
• Porter-Duff compositing algebra (Siggraph 84)
• Morphing (Beier-Neely, Siggraph 92)

17.6 in textbook covers some aspects, but not all
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Blue Screen Matting

• Photograph or create image of object against blue
  screen (blue usually diff from colors like skin)
  
• The extract foreground
  (non-blue pixels)
  
• And add (composite) to new
  image
  
• Problem aliasing hair
  (no notion
  of partial
  coverage/blue)

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Outline

• Compositing or combining images
  Fundamental problem in graphics images from
  different sources, put them together
  
• Blue screen matting
• Alpha channel
• Porter-Duff compositing algebra (Siggraph 84)
• Morphing (Beier-Neely, Siggraph 92)

17.6 in textbook covers some aspects, but not all
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Alpha Channel

• In general, 32 bit RGBa images
• Alpha encodes coverage (0transparent, 1opaque)
• Simple compositing

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Alpha Channel
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Pixels with Alpha Conventions

• Premultiplication
• Color C (r,g,b) and coverage alpha is often
  represented as
  
• One benefit color components aF directly
  displayed
  
• What is ( a , C ) for the following?
• (0, 1, 0, 1) Full green, full coverage
• (0, ½ , 0, 1) Half green, full coverage
• (0, ½, 0, ½) Full green, half (partial)
  coverage
  
• (0, ½, 0, 0) No coverage

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Compositing with Alpha
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Opaque Objects

• In this case, a controls the amount of pixel
  covered (as in blue screening).
  
• How to combine 2 partially covered pixels? 4
  possib. outcomes.

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Outline

• Compositing or combining images
  Fundamental problem in graphics images from
  different sources, put them together
  
• Blue screen matting
• Alpha channel
• Porter-Duff compositing algebra (Siggraph 84)
• Morphing (Beier-Neely, Siggraph 92)

17.6 in textbook covers some aspects, but not all
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Compositing Algebra

• 12 reasonable combinations (operators)

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Computing Colors with Compositing

• Note that coverages shown previously only
  examples
  
• In practice, we only have a, not exact coverage,
  so we assume coverages of A and B are
  uncorrelated
  
• Question is how to compute net coverage for
  operators previously?

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Example C A over B
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Image Compositing Example
Jurassic Park 93
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Technical Academy Awards 96

• Scientific and Engineering Achievement Award
• Alvy Ray Smith, Ed Catmull, Thomas Porter, Tom
  Duff for their pioneering inventions in
  digital image compositing
  
• Technical Achievement Award
• Computer Film Co. For their pioneering efforts in
  the creation of the CFC digital film compositing
  system
  
• Gary Demos, David Ruhoff, Can Cameron, Michelle
  Feraud for their pioneering efforts in the
  creation of the Digital Productions digital film
  compositing system
• Douglas Smythe, Lincoln Hu, Douglas S. Kay,
  Industrial Light and Magic Inc. for their
  pioneering efforts in the creation of the ILM
  digital film compositing system

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Outline

• Compositing or combining images
  Fundamental problem in graphics images from
  different sources, put them together
  
• Blue screen matting
• Alpha channel
• Porter-Duff compositing algebra (Siggraph 84)
• Morphing (Beier-Neely, Siggraph 92)

17.6 in textbook covers some aspects, but not all
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Examples

• Famous example Michael Jackson Black and White
  Video (circa 1991).
  
• Unfortunately, I couldnt find a version of this
• Easy enough to implement assignment in many
  courses (we show example from CMU course)
  
• No music, but the good poor mans alternative

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Examples
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Simple Cross-Dissolve
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The idea in morphing

• User marks line segments
• These are used to warp image 1 and image 2
• Images are then blended
• Key step is warping
• Why is it needed? Why not just cross-dissolve or
  blend two images based on alpha (how far between
  them)
  
• How is it to be done with line segments?

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Beier-Neely examples
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(No Transcript)
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Feature-Based Warping

• To warp image 1 into image 2, we must establish
  correspondence between like features
  
• Then, those features transform (and rest of image
  moves with them)
  
• In Beier-Neely, features are user-specified line
  segments (nose, face outline etc.)
  
• Warping is an image transformation (generally
  more complex than scale or shift, but same basic
  idea)
  
• Morphing takes two warped images and
  cross-dissolves

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Warping with Line Segments

• We know how line warps, but what about whole
  img?
  
• Given p in dest image, where is p in source
  image?

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Warping with one Line Pair

• What happens to the F?

Translation!!
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Warping with one Line Pair

• What happens to the F?

Similar ideas apply to rotation,
other similarity transforms
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Warping with Multiple Line Pairs
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Details
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Weighting effect of each line pair
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Warping Pseudocode
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Morphing Pseudocode
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Examples