Project 4: Face Morphing

Single Face Morph

I was tasked with computing the face morph between nfeltman (myself) and phoskins. The source images and a 50% blend are shown below:
nfeltman 50% blend phoskins

I found that the key to good results was using many control points. I used 119. A full video of the morph can be found here at 30 fps and here at 5 fps, and each frame can be found as a picture here.

Class Face Database

I used a database of 18 images. Since data quality is important, I manually adjusted all of the control points to make the meshes consistent with one another. I also added control points around the border of the image. For example:

All of the source images and control points can be found here.

Population Averages

I first split the class into two populations: men and women. The indeces and average faces of these subpopulations and the full population are shown:
Men All Women
[1 3 4 5 6 8 9 10 11 13 15 16 17] 1...18 [2 7 12 14 18]

I additionally split the men into two catagories: those of eastern Asian descent, and those of European and south Asian descent. The indeces and facial averages for thesee subpopulations are shown:
East Asian Men Non-East Asian Men
[1 4 9 15 16] [3 5 6 8 10 11 13 17]

Finally I show examples of the average face warped to my geometry, as well as my face warped to the average geometry:
Average Face Average Geometry

Bell And Whistle -- Adjusting My Geometry

I present a geometric morph of my face that increase my variation from the average:
Base Charicature (+70%) Charicature (+120%)

I present several morphs of the geometry of my face based on subpopulation averages:
Masculinized Feminized Male-Asianized