I’ve spent the majority of my time at the vision sciences laboratory making faces for two new measures of facial recognition. For the first measure, I made more than 2000 faces based on 50 “parent” faces. The derived faces were based on the same characteristic features as their parent, except that I manipulated gender for each face. Now we have a library of faces that subtly vary in gender. We’ll be using these faces to see how well people can identify gender based on facial features, as well as measure the sensitivity of their gender perception skills.

The second library I made was similar to the first, except I kept gender constant and varied age instead. It’s a lot of fun to scroll through the faces and see them get older and younger.

I’ve also made a third library, although it isn’t face oriented. This library is composed of unfamiliar objects. We might use the objects in this library to develop a measure of how well people can recognize novel objects. Or not. We’ll see!

As of right now, none of the studies I’m involved in have started recruiting participants.

However, next week I’ll start screening subjects for the prosopagnosia family study.  At some point in the not-so-distant-future, I’ll be administering a battery of facial recognition tests for the machine learning study.

I’ve been contributing the development of new measures of how we perceive gender and age through faces by making more than 2000 variations of “gendered” faces and 800 variations of “aged” faces.  It feels good to be directly contributing to the project!

It looks like I will be working on three projects this summer:

1) Investigating genetic and cognitive trends in families with prosopagnosia.

2) Developing new measures of how people determine age and gender based on facial information.

3) Collecting data for a study on machine learning of facial recognition.

I don’t know much about machine learning so I’ll be spending the next few days reading up on neural networks.  It’s really great being in a place where reading journal articles qualifies as work!  (More evidence I should just go to graduate school.)