Eye tracking research is a growing area and the fields as where eye trackingcould be used in research are large. To understand the eye tracking data dif-ferent filters are used to classify the measured eye movements. To get accu-rate classification this thesis has investigated the possibility to measure bothhead movements and eye movements in order to improve the estimated gazepoint.The thesis investigates the difference in using head movement compensationwith a velocity based filter, I-VT filter, to using the same filter without headmovement compensation. Further on different velocity thresholds are testedto find where the performance of the filter is the best. The study is made with amobile eye tracker, where this problem exist since you have no absolute frameof reference as opposed to when using remote eye trackers. The head move-ment compensation shows promising results with higher precision overall.