Abstract. Eye-gaze tracking is an aspect of human-computer interaction still growing in popularity,. Tracking human gaze point can help control user interfaces and may help evaluate graphical user interfaces. At the same time professional eye-trackers are very expensive and thus unavailable for most of user interface researchers and small companies. The paper presents very effective, low cost, computer vision based, interactive eye-gaze tracking method. On contrary to other authors results the method achieves very high precision (about 1.5 deg horizontally and 2.5 deg vertically) at 20 fps performance, exploiting a simple HD web camera with reasonable environment restrictions. The paper describes the algorithms used in the eye-gaze tracking method and results of experimental tests, both static absolute point of interest estimation, and dynamic functional gaze controlled cursor steering.

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Abstract-Head pose estimation from camera images is a computational problem that may influence many sociological, cognitive, interaction and marketing researches. It is especially crucial in the process of visual gaze estimation which accuracy depends not only on eye region analysis, but head inferring as well. Presented method exploits a 3d head model for a user head pose estimation as it outperforms, in the context of performance, popular appearance based approaches and assures efficient face head pose analysis. The novelty of the presented approach lies in a default head model refinement according to the selected facial features localisation. The new method not only achieves very high precision (about 4• ), but iteratively improves the reference head model. The results of the head pose inferring experiments were verified with professional Vicon motion tracking system and head model refinement accuracy was verified with high precision Artec structural light scanner.

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