Computing Midway Face

First, we get the points for both images and take the average to get the average shape. We get the triangulation of the average shape For each triangle, we solve the system of equations y = Tx, where y is the original points of the triangle and x is the average points of the triangle to get the inverse transform T from the average shape to the original images. We do this, so we can get the color values from the original images. However, it is possible we land on a fractional value for a pixel, so we have to interpolate between pixel values to get the correct color. We do a weighted sum of the color values for each image, which is the average for the midway face.

Morph Sequence

Instead of taking the average as before with the midway face, we instead interpolate between 0 and 1 to get a weighted shape and do the same algorithm, and for cross dissolving, we also interpolate between 0 and 1, instead of taking the average. We stack 45 frames at 30 fps to create a gif of morphing from 1 face to another.

The Mean Face of Danes

I used the Danes dataset for morphing as shown below. To get the average face image, we do the morphing as above into the average shape, and then average the interpolated colors across the images.

Caricatures: Extrapolating from the Mean

I increase the interpolation value to be outside the range [0,1] to do an extrapolation on the population mean of the Danes for the image morphing.

Bells and Whistles:

I decided to turn Jay Z into a Burmese man.