Gaze estimation is a classic problem of machine vision, which can now be solved by one computer training another.
Eye contact is one of the most powerful forms of nonverbal communication. If avatars and robots are ever to exploit it, computer scientists will need to better monitor, understand, and reproduce this behavior.
But eye tracking is easier said than done. Perhaps the most promising approach is to train a machine-learning algorithm to recognize gaze direction by studying a large database of images of eyes in which the gaze direction is already known.
The problem here is that large databases of this kind do not exist. And they are hard to create: imagine photographing a person looking in a wide range of directions, using all kinds of different camera angles under many different lighting conditions. And then doing it again for another person with a different eye shape and face and so on. Such a project would be vastly time-consuming and expensive.
