How does Head Stability Improve Eye Tracking Accuracy?

When conducting research, the accuracy of the data is critical to the validity of the results. In the field of eye tracking research, we are always searching for ways to improve our techniques and make the data we collect as legitimate as possible. A German blogger, Markus Weber, discussed data accuracy of eye tracking in a post on the blog site, Another Useful Blog.

Weber writes that one essential part of the eye tracking setup is the camera that captures light reflected by the eye. From there, it determines gaze direction. If the eye tracker is not head-mounted, the camera will often be positioned statically, attached or mounted to a computer monitor. The movements of the head can cause the captured image to go out of focus until the auto-focus of the camera has corrected the situation, which can in turn influence the precision of measurement. This sometimes makes for inaccuracies in the data. In addition, sideways movements of the head can make the camera lose the image completely, and this is usually addressed by making the camera follow the captured image up to a certain extent.

When head movement exceeds the range that the camera tracking can compensate for, the camera can either remain at the position where the image was last captured or return to a default position. As soon as a reflection is captured again, the data acquisition continues, but for that interval time, no data can be collected.

Oftentimes, head movements are likely to happen whenever the person deals with interactive systems where they aren’t sitting passively in front of a screen. With interactive material, head movements and the corrective mechanisms Weber writes about are likely to come into play. Until respective corrections are completed, it’s impossible to depend too much on the accuracy of the data collection.

If the head is fixated, measurement precision can improve to some extent. With a chin rest or something similar, head movements can be effectively eliminated but it often results in a more unnatural, uncomfortable situation for the person whose gaze is being measured. As Weber writes: “imagine sitting in front of your computer without being able to move your head.” Talking is also a challenge and makes for more limitations during the study.

What You Always Wanted to Know About Eye Tracking – Part 2: Data Accuracy

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