To define keypoints for warping, I used ginput to collect 47 points on the image, including 4 points in the corners.
We can compute the 'mid-way face' of two images by weighing them differently each time.
Now, by producing multiple 'mid-way faces' by increasing the warp fraction and weighing the pixels we can create a MORPH
By calculating the average shape of a population's faces, and warping each of the images to the average shape, we get to the 'mean face'.
I used the FEI Face Database, and used images of 20 females to get an average female face shape. Here are examples of warped images:
Now, by adding up all the warped images as above, we can get the mean faces.
Warping Me(A Generic Man Image) to Mean and Mean to Me(A Generic Man Image)
Extrapolating from the mean female face, we try to exagerate certain features to create caricatures:
I morphed a man's face to the mean female face to see how a gender change would look like for him. This is the result: a) His jawline has become much software and the shape of the face is much narrower like that of females. b) His hair on the sides is warped to become slightly longer. c) Because of his glasses it was harder to warp the area around his eyes