My introduction to AI class required us to write a classifier for people in the news (20 different images of 10 different people). We were given the location of the people's faces, but we were able to get 60% accuracy using SVMs and the 32x32 block of pixels (nose, eyes, mouth region). This was the "baseline" system. Some systems were getting nearly 85+%. I must admit though, that this was a restricted dataset, but the faces were not all looking straight ahead the way eigenfaces are, and I'm sure with enough data, and enough features that sort of CAPTCHA could be defeated a large percentage of the time.
You are confusing two different tasks, identifying a person out of a small comparison group is relatively easy - just deconstruct the face & compare certain facial features. There was a ton of research on the subject and even some working commercial products (my schools AI lab uses one we built as a lock).
Identifying gender is significantly harder.
You want something a lot harder, have them click on the picture of the more attractive person, use data from a hotornot type site (just make sure the data isn't public). Good luck solving that with Support Vector Machines. If you want to generate more data just use build RE-CAPTCHA type system.
I don't see why it'd be harder with good features, and after looking at the article again, 35% accuracy was considered a success. Obviously, I'm not as qualified as you in this sense, but it seems logical based on results I've seen (again, admittedly not the same quality as you've probably seen).
I checked on the "obviously, I'm not as qualified as you in this sense" by looking at the user info, and I remembered that "Ideas to monetize new artifical intelligence" thread... so Marcus, sorry if it's offtopic, but how did you solve that problem? Are you doing captchas maybe? :)
In a way I understand trying to apply the algorithm manually for each client is wasteful, negotiation with each client is tiring especially when its with a 7B company.
I'm thinking about using the idea I got of building a web-service around it, and letting people find their own uses for it.
