An electronic device and a method of operating the electronic device are provided. The electronic device includes a proximity detector; an iris recognition module; a memory; and a processor electrically connected to the proximity detector, the iris recognition module, and the memory, wherein the processor is configured to execute an iris recognition operation based on the iris recognition module; determine proximity of an object based on the proximity detector while the iris recognition operation is performed; and, if the proximity of the object includes within a set reference range, stop the iris recognition operation.

A user recognition method that uses an iris is provided. The user recognition method includes generating a first mask for blocking a non-iris object area of an iris image, generating a converted iris image, in which the non-iris object area is blocked according to the first mask, generating a second mask for additionally blocking an inconsistent area, in which quantization results of the converted iris image are inconsistent, by adaptively transforming the first mask according to features of the converted iris image, obtaining an iris code by quantizing pixels included in the iris image, obtaining a converted iris code, in which portions corresponding to the non-iris object area and the inconsistent area are blocked, by applying the second mask to the iris code, and recognizing a user by matching a reference iris code, stored by the user in advance, to the converted iris code.

A station device in a biometric pre-identification system uses identity to perform one or more actions. Identities are determined (such as via a backend) using biometric information. A biometric pre-identification device obtains biometric information and/or a digital representation thereof from a person approaching the station device. The biometric pre-identification device transmits such to the station device, facilitating the station to begin and/or perform various actions. The station device begins or performs the actions using the identity determined based on the biometric information before the person arrives at the station device.

Embodiments pertain to a method for characterizing a droopy upper eyelid performed on a computer having a processor, memory, and one or more code sets stored in the memory and executed in the processor. The method may comprise capturing an image of a patient's facial features comprising an eye and a droopy upper eyelid; identifying at least one geometric feature of a pupil of the eye within the image; and determining, based on the at least one geometric feature, whether the droopy upper eyelid is vision impairing or not, or whether the droopy upper eyelid is more likely vision impairing than not vision-impairing.

Systems and methods for iris authentication are disclosed. In one aspect, a deep neural network (DNN) with a triplet network architecture can be trained to learn an embedding (e.g., another DNN) that maps from the higher dimensional eye image space to a lower dimensional embedding space. The DNN can be trained with segmented iris images or images of the periocular region of the eye (including the eye and portions around the eye such as eyelids, eyebrows, eyelashes, and skin surrounding the eye). With the triplet network architecture, an embedding space representation (ESR) of a person's eye image can be closer to the ESRs of the person's other eye images than it is to the ESR of another person's eye image. In another aspect, to authenticate a user as an authorized user, an ESR of the user's eye image can be sufficiently close to an ESR of the authorized user's eye image.

Provided is a method and apparatus for eye tracking. An eye tracking method includes detecting an eye area corresponding to an eye of a user in a first frame of an image; determining an attribute of the eye area; selecting an eye tracker from a plurality of different eye trackers, the eye tracker corresponding to the determined attribute of the eye area; and tracking the eye of the user in a second frame of the image based on the selected eye tracker, the second frame being subsequent to the first frame.

A system for contemporaneously calibrating a gaze-tracking system and authorizing access to a first other system can include a processor and a memory. The memory can store a preliminary operations module, an authorization module, and a gaze-tracking module. The preliminary operations module can include instructions to compare a trajectory, of a point of gaze of an eye, with a pattern associated both with a calibration of the gaze-tracking system and with a first authorization process, that excludes an iris recognition process, for the first other system. The authorization module can include instructions to cause an access to the first other system to be authorized. The gaze-tracking module can include instructions to: (1) cause the gaze-tracking system to be calibrated and (2) cause, in response to the gaze-tracking system being calibrated, the gaze-tracking system to be configured to be a user interface for a second other system.

An ophthalmic image of an evaluation target is acquired, a plurality of subsection images is extracted from the ophthalmic image, a state of a subject's eye is predicted for each of the subsection images based on a learned model in which learning has been performed in advance regarding extracting a plurality of subsection images from an ophthalmic image for learning, and predicting a state of a subject's eye for the each of subsection image by machine learning using correct answer data related to a state of each subsection image, and the subsection image is extracted from the ophthalmic image so as to have an image size corresponding to a state of a subject's eye of an evaluation target.

Disclosed are a face image and iris image acquisition method and device, a computer-readable readable storage medium and an apparatus. The method includes rotating the first tripod head to force the face lens and the iris lens to be in acquisition positions; capturing a first face image and a first iris image simultaneously by the face lens and the iris lens; and locating the iris in the first iris image, and if no iris is located, determining whether a condition of light-avoiding rotation is satisfied, and if the condition is satisfied, rotating the second tripod head to adjust an angle or a position of the supplementary light source to enable a light spot region to avoid an iris region.

Examples are described herein for establishing private communication channels. In various examples, camera-acquired eye tracking data if participants in a first video conference call may be monitored. Based on the monitoring, it may be determined that gazes of a subset of the participants collectively satisfy a criterion, wherein the subset includes a plurality of the participants in the first video conference call. In response to the determining that the gazes of the subset of participants collectively satisfy the criterion, a private second video conference call between the plurality of the participants is established.