Abstract: There is provided a method, system, and non-transitory computer-readable storage medium for classifying glints using an eye tracking system of a head-mounted device, by obtaining the position of any glint present in a current image of the first eye; obtaining a dataset indicative of the respective position of at least one glint detected in one or more previously captured images of the first eye; and, for each glint present in current image, determining if the position of the glint corresponds to the position of a glint in the dataset and, if the positions correspond, classify the glint as a static glint. The static glints may be excluded from further processing in the eye tracking system. If there has been a movement of an eye of the user of the head-mounted device, embodiments may further comprise updating the dataset based on the current image.

Abstract: The invention is related to a method for calibrating an eye tracking device within a head-mounted display (HMD) comprising the steps of acquiring with the HMD via an image sensor, at least one optical target image from an optical target, wherein the optical target contains image points in a pattern, indexing image points within the optical target image wherein the image points are indexed by, selecting a rigid region of the optical target image, assigning indices to image points within the rigid region, fitting a polynomial approximation function to at least one column and one row of the image points of the region, predicting the location of at least one image point using the fitted polynomial approximation function, assigning the predicted image point an index, inputting indexed image points into an optimization algorithm that calculates a hardware calibration of the HMD, and writing hardware calibration values calculated from the optimization algorithm to the HMD unit.

Abstract: There is provided a method, system, and non-transitory computer-readable storage medium for classifying glints using an eye tracking system of a head-mounted device, by obtaining the position of any glint present in a current image of the first eye; obtaining a dataset indicative of the respective position of at least one glint detected in one or more previously captured images of the first eye; and, for each glint present in current image, determining if the position of the glint corresponds to the position of a glint in the dataset and, if the positions correspond, classify the glint as a static glint. The static glints may be excluded from further processing in the eye tracking system. If there has been a movement of an eye of the user of the head-mounted device, embodiments may further comprise updating the dataset based on the current image.