Part of something I'm working on (or rather begin working on) involves white box approaches to facial recognition. I previously worked on something for character recognition using scene segmentation and neural networks but for faces I'm trying to challenge myself by not using neural networks or other AI strategies.
Consider a potential algorithm that takes a headshot photo as an input and the outputs are some metrics about said face. Like the eye color, skin color, hair color, philtrum width and height, distance between eyes, etc. What techniques exist that I should look into on how to implement this?
My concern is mostly with feature extraction from points of interest from a face. I think my difficulty is algorithmically describing the composition of a face to pull metrics.