Face Recognition by Computer and Humans

Tags

face, INFO411, pattern recognition

Let's Face it.

Faces are fascinating. Not less is face recognition research.
This new article on IEEE Computers Magazine is a very good read, giving good background but also pointing to future directions. Very insightful. Highly recommended.
Here are a few directions I noted:
- on a psychological side, what is the role of top-down expectation? Will it help fast identification in a ‘many faces’ scenario (see my last post)? The familiarity of the face counts?
- how can a camera network do face recognition? The multi-view fusion should be done on the face image, or on face recognition results?

Someone volunteers a 411 talk on this subject?

So many faces…

Tags

face, saliency

Spotting a face out from a cluttered background may be an effortless thing, but have you ever tried searching out a friend’s face in a group photo, and you wondered why it took you so long?

In this Face Facts: People Don’t Stand Out In A Crowd article, this crowding effect was first studied for high-level stimuli such as faces. More details are available from this JoV paper by Bressler and Whitney.

What does this relate to our research in modeling high-level saliency in perception? With many saliency points contending our focus, surely the saliency level of these points will cancel each other, perhaps using some inhibition mechanism.

On the other hand, can we find a signature space for faces, so that a face hunt among a crowd can speed up, perhaps using a multi-resolution approach, so that identification (and localization) of a certain face can be more efficient, without going through scanning through all the faces one after another on the finest resolution?

Contrary to the notion that a face is processed as an image in our vision system, this JoV paper treats faces mainly as horizontal lines or bar-codes!

Faces are interesting, aren’t they?