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DIGITAL IMAGE
MORPHING THROUGH
“FIELD MORPHING”

Ankur Sakhuja
Example
Block Diagram for Algorithm Workflow
Generating an intermediate frame

  Image IS                     Image I1
                 Fs → F warp
  Feature Spec                 Feature
  Fs                           Spec F




                                                           Morph
                                  Color interpolate
                                                           Image




                               Image I2                            Image IT
                                                  FT → F warp
                               Feature                             Feature
                               Spec F                              Spec FT
Algorithm overview

 Basic motivation: specification of feature points as lines – more expressive and
  intuitive
 Line features specified in both source and target images and correspondence
  established
 For every intermediate position in morph sequence, a line feature set is
  generated by interpolating the two sets
 Between source and intermediate line feature sets:-
 Every pair of line features represents a coordinate transformation for a point
  from source to target image – results in some spatial displacement
 A weighted sum of displacements due to all line pairs gives net displacement
  of a point – the total warp function
 Warp both source and target images to get two intermediate images
 Color interpolate to obtain the morph image
 Repeat for every position in the sequence to obtain the morph sequence
The Math:
Pixel transformation
specified by single
pair of line segments
The Math (contd):
Pixel transformation specified by two pairs of line segments
The Math (contd):
weighting factor for combining transformations of multiple line segment pairs




                                                                                           b

Weighting factor for combining displacements:                                   length p
                                                                    Weight
                                                                                a dist
Algorithm Pseudocode
• For each pixel X in the destination
•     DSUM = (0,0)
•     weightsum = 0
•     For each line Pi Qi
•          calculate u,v based on Pi Qi
•          calculate X'i based on u,v     and Pi'Qi'
•          calculate displacement Di = Xi' - Xi for this line
•          dist = shortest distance from X to Pi Qi
•          weight = (lengthp / (a + dist))b
•          DSUM += Di * weight
•          weightsum += weight
•     X' = X + DSUM / weightsum
•     destinationImage(X) = sourceImage(X')
MATLAB Implementation and Results
Reference


  1.   Beier, T. and Neely, S. 1992. Feature-based image metamorphosis. In
       Proceedings of the 19th Annual Conference on Computer Graphics and
       interactive Techniques

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Digital Image Morphing through Field Morphing

  • 1. DIGITAL IMAGE MORPHING THROUGH “FIELD MORPHING” Ankur Sakhuja
  • 3. Block Diagram for Algorithm Workflow Generating an intermediate frame Image IS Image I1 Fs → F warp Feature Spec Feature Fs Spec F Morph Color interpolate Image Image I2 Image IT FT → F warp Feature Feature Spec F Spec FT
  • 4. Algorithm overview  Basic motivation: specification of feature points as lines – more expressive and intuitive  Line features specified in both source and target images and correspondence established  For every intermediate position in morph sequence, a line feature set is generated by interpolating the two sets  Between source and intermediate line feature sets:-  Every pair of line features represents a coordinate transformation for a point from source to target image – results in some spatial displacement  A weighted sum of displacements due to all line pairs gives net displacement of a point – the total warp function  Warp both source and target images to get two intermediate images  Color interpolate to obtain the morph image  Repeat for every position in the sequence to obtain the morph sequence
  • 5. The Math: Pixel transformation specified by single pair of line segments
  • 6. The Math (contd): Pixel transformation specified by two pairs of line segments
  • 7. The Math (contd): weighting factor for combining transformations of multiple line segment pairs b Weighting factor for combining displacements: length p Weight a dist
  • 8. Algorithm Pseudocode • For each pixel X in the destination • DSUM = (0,0) • weightsum = 0 • For each line Pi Qi • calculate u,v based on Pi Qi • calculate X'i based on u,v and Pi'Qi' • calculate displacement Di = Xi' - Xi for this line • dist = shortest distance from X to Pi Qi • weight = (lengthp / (a + dist))b • DSUM += Di * weight • weightsum += weight • X' = X + DSUM / weightsum • destinationImage(X) = sourceImage(X')
  • 10. Reference 1. Beier, T. and Neely, S. 1992. Feature-based image metamorphosis. In Proceedings of the 19th Annual Conference on Computer Graphics and interactive Techniques