The quality of the images is ultimately determined by the cameras’ position relative to the eye - a good view of the eyes will produce better gaze point estimations. Fortunately, the Pro Glasses 2 Controller software has two features to help the researcher work out the position of the frame on the participant's head: the Adjustments tool (a.k.a. Track Status), and Eye Images tool.
The Adjustments tool provides a simplified view of the positioning of the eyes inside the glasses. The white dots in the image show the location of the pupil in the field of view of the cameras, the large circle. In order for the eyes to be in the field of view of the cameras the dots should stay inside of the circles, and as close to the center of the circles as possible when looking straight ahead.
More importantly, the researcher also has the option to display the eye images recorded by the cameras, when live viewing a recording. These images can be used to inform whether the glasses are positioned correctly, but also help troubleshoot any potential issues with data quality.
You can use the images to check:
Figure 1 illustrates a case where the glasses are a bit too low on the nose. Although the pupil is visible by all cameras, most of the illumination ends up on the lower eyelid and cheek, resulting in a too low contrast of the pupil. That is, the iris is also very dark and the borders of the pupil are not easily distinguishable from the iris. Additionally, some glints are covered. This is not a major problem as long as some glints are seen, but to be safe we prefer to have more glints in view if we can. This positioning problem is easily fixable by exchanging the nose piece to one more compatible with your participant.
Figure 2 shows the eye images after the nose piece exchange and how this results in better eye images. Most importantly, the eyes are properly illuminated and the pupil can be seen in great contrast. Also, more glints are in view.
During your test it is useful to validate the calibration as soon as you start the recording. This procedure will enable you to check the performance of the eye tracker before collecting the bulk of the data, and document the data quality in the recording, providing you the possibility to refer back to it when needed.
A validation can easily be done by instructing the participant to look at several known positions around the field of view, for example: straight-ahead, up to the left, up to the right, down to the left, down to the right. The offset of the gaze cursor from the known target gives an indication of what offset to expect. If we also consider the eye images, it is possible to see if the error is expected from the calibration, or if it is due to some problem from the eye image. Examples of such errors could be: