Morph 1: Two Danish scientists
Source with correspondence points
Target with correspondence points
Source morphed to midway face (t = 0.5)
Target morphed to midway face (t = 0.5)
Morph 2: Me and Constance Wu
I used a dataset of 37 Danish scientists to produce the mean face of the Danish scientist population. First, I computed the correspondence points of the average Danish scientist by taking the average of all the correspondence points of each scientist. Then I warped each scientist into the average shape. Finally, I took the average pixel intensities of all the averaged faces to produce the final average Danish scientist face.
07-1m Morphed Into Average Face Shape
08-1f Morphed Into Average Face Shape
The Average Danish Scientist Face
Me to Average Danish Scientist
Average Danish Scientist to Me
Taking the previously computed average Danish computer scientist's Face (call this A), I subtract the correspondence points of my own face (call this B) from the points of A to find the feature differences. We can then use these feature differences to produce a caricature by extrapolating from the mean using the equation: caricature_pts = A + alpha * (B - A), where alpha is greater than 1.
Alpha = 1.3
Alpha = 1.5
Alpha = 1.8
Changing Myself to a Dutch Woman
I found an image of the average Dutch woman and decided to change myself to her! Below are the results of 1) changing only my shape, 2) changing only my color, and 3) both color and shape. Each image was morphed/cross-dissolved at 50%.
Average Dutch Woman
Me with 50% Shape
Me with 50% Color
Me with 50% Color and Shape
Here is me at ages 5, 8, 14, and 21!