Abstract: An eye tracking system comprising a processor configured to: receive a plurality of images of an eye from a camera, each image comprising an illuminated sub-region of a cornea of the eye, the illuminated sub-region comprising: a first corneal reflection of a first light source from a surface of the illuminated sub-region; and a second corneal reflection of a second light source from the surface of the illuminated sub-region; for each image, determine a three-dimensional, 3D, position of the first corneal reflection and a 3D position of the second corneal reflection based on a position of the camera, a position of the first light source, a position of the second light source, positions of the first and second corneal reflections in the image and a corneal surface model for the illuminated sub region; and output a topographical profile of the cornea based on the 3D positions determined for each image.

Abstract: Computer-generated image data is presented on first and second displays of a binocular headset presuming that a user's left and right eyes are located at first and second positions relative to the first and second displays respectively. At least one updated version of the image data is presented, which is rendered presuming that at least one of the user's left and right eyes is located at a position different from the first and second positions respectively in at least one spatial dimension. In response thereto, a user-generated feedback signal is received expressing either: a quality measure of the updated version of the computer-generated image data relative to computer-generated image data presented previously; or a confirmation command. The steps of presenting the updated version of the computer-generated image data and receiving the user-generated feedback signal are repeated until the confirmation command is received.

Abstract: An eye tracking system is provided that detects the presence of problematic blobs in an image captured by the system and removes these problematic blobs by switching off illuminators. Problematic blobs may be those obscuring the pupil of the eye of the user. Each blob is detected in a first image by the use of at least one first criterion, and then an illuminator is switched off. After the illuminator is switched off, at least one second criterion is used to identify blobs in a subsequent image. This process may be repeated until the illuminator causing the problematic blob is identified.

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: Computer-generated image data is presented on first and second displays of a binocular headset presuming that a user's left and right eyes are located at first and second positions relative to the first and second displays respectively. At least one updated version of the image data is presented, which is rendered presuming that at least one of the user's left and right eyes is located at a position different from the first and second positions respectively in at least one spatial dimension. In response thereto, a user-generated feedback signal is received expressing either: a quality measure of the updated version of the computer-generated image data relative to computer-generated image data presented previously; or a confirmation command. The steps of presenting the updated version of the computer-generated image data and receiving the user-generated feedback signal are repeated until the confirmation command is received.