Morphing involves transitioning between images by partitioning them into regions based on feature points like eyes and mouths. Face morphing algorithms find these points to warp and cross-dissolve images, transforming one face into another. Hollywood and Disney use face morphing for special effects and animation by speeding up transitions between character expressions or individuals. The process involves pre-processing, feature finding, image partitioning, coordinate transformations, and cross-dissolving regions to blend facial features between images.

2. Morphing is tweening between different
images.
Morphing derives from “metamorphosis,” an
ancient Greek word meaning “transformation.”

3.  How’s Face Morphing done?
 Algorithms explains the extra feature of points on face
and based on these feature points ,images are
partitioned and morphing is performed
 Algorithms has been used to generate morphing
between images of face of different people as well as
between images of face of individuals

4.  Dissolving (creates transition morphs)
 Warping (creates distortion morphs)

5.  Where do we use face morphing?
 Hollywood film makers use novel
morphing technologies to generate special
effects
 Disney uses morphing to speed up the
production of cartoons
 photoshop

6.  Procedures Involved:
 Pre-Processing
 Feature Finding
 Eye-finding
 Mouth-finding
 Image Partitioning
 Coordinate Transformations
 Cross-Dissolving

7. Feature Finding
 Our goal was to find 4 major feature points, namely the
 two eyes, and
 the two end-points of the mouth.
 Within the scope of this project, we developed an eye-
finding algorithm that successfully detect eyes at 84% rate.

8.  Eye-finding
 We assume that the eyes are more complicated than
other parts of the face
 we first compute the complexity map of the facial
image by sliding a fixed-size frame and measuring the
complexity within the frame in a "total variation"
sense.

9. Eye finding algorithm

10.  Image Partitioning:
 Our feature finder can give us the positions of the eyes and
the ending points of the mouth, so we get 4 feature points
 Beside these facial features, the edges of the face also need
to be carefully considered in the morphing algorithm
 totally we have 10 feature points for each face

11. • Based on these 10 feature points, our face-morpher partitions
each photo into 16 non-overlapping triangular or
quadrangular regions

12. • Cross-Dissolving
• After performing coordinate transformations for each of the
two facial figures, the feature points of these figures are
matched. i.e., the left eye in one figure will be at the same
position as the left eye in the other figure.
• To complete face morphing, we need to do cross-dissolving as
the coordinate transforms are taking place. Cross-dissolving is
described by the following equation,

13. The following example demonstrates a typical morphing
process
original images of Ally and Lion

14. Cross-dissolve the two images to
generate a new image. The new face
possesses the features from both and
the lion's Ally's faces

15. Morphing between faces of different
cases
 Human and Animal (Lion)

16.  Man And Man

17.  Man and woman

18.  Morphing between different images of the same
person
Happy <===
===> Angry

19.  Conclusion
 We believe that feature extraction is the key
technique toward building entirely automatic face
morphing algorithms
 we demonstrated that face morphing algorithm
can help generate animation.
 Ideally speaking , the more feature points we
can specify on the faces, the better morphing
results we can obtain