PUPIL VISUAL TRACKING ALGORITHMS FOR AUTOMATED STATIC PERIMETRY SYSTEMS
Keywords: Static Perimetry, Segmentation, Tracking, Optical Flow, Weighted Average
Abstract. Some diseases, for instance, a glaucoma, cause visual field defects. For the timely diagnostics of such defects, various methods are used. One of the state-of-the-art diagnostic methods is automated static perimetry. The method of static perimetry consists in the light sensitivity determination in different parts of the visual field using stationary objects of variable luminosity. When scanning the visual field in this way, an important factor is the control of gaze fixation at the fixation point. The greatest accuracy in determining the gaze fixation position is achieved by the method of the pupil visual tracking using a video camera.
In this paper, four groups of visual tracking algorithms are considered: segmentation-based methods, correlation methods, methods based on optical flow and on weighted average. An experimental comparison of these methods was carried out using the base of video recordings obtained in the automatic static perimetry apparatus. On these videos the ground truth tracks of pupil were marked. The comparison was conducted according to two criteria: center location error and tracking length. It is shown that only the weighted average method has an acceptable tracking length.