This article is the fifth of a series in which I explain what my research is about in (I hope) a simple and straightforward manner. For more details, feel free to check the Research section.
In my last post we faced a hard problem: If a person visits a museum, for instance, we could give them information on the piece they are looking at. But computers don't have eyes! We could use a camera, sure, but that only works if there is only one art piece nearby. If there are several paintings close to each other, how do we decide which one of them is the interesting one?
One way is through what we call eye-tracking. This technology works like a regular camera, but with a catch: it doesn't only look forward, but it also looks backwards, at you! If you wear one of these so-called eye-trackers, it follows the movement of your eyes and records not only the entire scene (like a regular camera) but also a tiny dot that points out what you were looking at. Some colleagues and I found that eye-movement gives you a very good guess at what has captured someone's attention. After all, if you are interested in something, you are probably looking at it.
But there's a complication: eye-trackers are bulky, expensive, and take a long time to set up. And most people feel uncomfortable knowing that someone is recording their activity all the time. It is safe to say that we won't be wearing eye-trackers for fun anytime soon, and that's not great: what good are our results, if no one wants to use them?
Luckily, a man named John Kelleher came up with a smart idea: whenever we are interested in an object, we look at it and get closer. He then applied this idea backwards: if we are looking in a certain direction and walking towards it, all we need to do is figure out what is right in front of us - that must be the object we care about. This technique is called visual salience, and it's a good alternative to an eye-tracker: rather than wearing expensive glasses, all we need to know is the direction in which they are walking. It might not be as effective, but it's good enough for us.
Following people's attention is important if we want our computers to cooperate with us: if a computer asks you to turn on the lights, but you start walking towards the fire alarm, it should warn you immediately that you are about to make a mistake. How to correct that mistake, however, is the topic of the next (and final) article.