Abstract: An eye tracking device that includes: an event-based optical sensor configured to receive radiation reflected off an eye of a user and produce a signal stream of events, each event corresponding to detection of a temporal change in the received radiation at pixels of the sensor; glint sources configured to send radiation to the eye that is reflected off the cornea and received by the sensor in the form of individual glints; a controller connected to the sensor and configured to receive the signal stream from the sensor and to generate: gaze information of the eye and first glint information of the glints, at a first instant of time; and second glint information of the glints at a second instant of time that is later than the first instant of time. The controller is configured to generate predicted gaze information at the second instant of time.

Abstract: An eye tracking device including an event-based optical sensor, configured to receive radiation reflected off an eye of a user and produce a signal stream of events, each event corresponding to detection of a temporal change in the received radiation at one or more pixels of said optical sensor, and a controller, which is connected to said optical sensor and configured to: a) receive the signal stream of events from the optical sensor, b) generate an inference frame based on the stream of events, c) utilize the inference frame as input to a machine learning module and operate the machine learning module to obtain output data, and e) extract from the output data information related to the eye of the user, wherein the controller is configured to generate the inference frame utilizing a first artificial neural network.

Abstract: An eye tracking device that includes: an event-based optical sensor configured to receive radiation reflected off an eye of a user and produce a signal stream of events, each event corresponding to detection of a temporal change in the received radiation at pixels of the sensor; glint sources configured to send radiation to the eye that is reflected off the cornea and received by the sensor in the form of individual glints; a controller connected to the sensor and configured to receive the signal stream from the sensor and to generate: gaze information of the eye and first glint information of the glints, at a first instant of time; and second glint information of the glints at a second instant of time that is later than the first instant of time. The controller is configured to generate predicted gaze information at the second instant of time.

Abstract: An eye tracking device including an event-based optical sensor, configured to receive radiation reflected off an eye of a user and produce a signal stream of events, each event corresponding to detection of a temporal change in the received radiation at one or more pixels of said optical sensor, and a controller, which is connected to said optical sensor and configured to: a) receive the signal stream of events from the optical sensor, b) generate an inference frame based on the stream of events, c) utilize the inference frame as input to a machine learning module and operate the machine learning module to obtain output data, and e) extract from the output data information related to the eye of the user, wherein the controller is configured to generate the inference frame utilizing a first artificial neural network.