There are a few systems high and low-cost ones for gaze tracking. Normally low-cost systems go in hand with low-resolution cameras. Here the image quality is poor, so the algorithms for detecting the gaze have to work more precisely. But how to test and analyse them correctly, when there is a bad image quality and no reference point known? The idea of this work is, to generate synthetic eye images, where the reference points are known, because they are mainly manually set and then to test and analyse the algorithms with these synthetic images. By switching on features like gaussian noise or a second glint-like reflection point, it is possible to stepwise approximate the synthetic images close to reality. In fact the experiments will lead to an improvement of the algorithms used in a low-resolution system environment.