Deep neural network for iris identification

    公开(公告)号:US10922393B2

    公开(公告)日:2021-02-16

    申请号:US15497927

    申请日:2017-04-26

    Abstract: 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.

    BLUE LIGHT ADJUSTMENT FOR BIOMETRIC SECURITY
    114.
    发明申请

    公开(公告)号:US20200272720A1

    公开(公告)日:2020-08-27

    申请号:US16870737

    申请日:2020-05-08

    Inventor: Adrian Kaehler

    Abstract: Systems and methods for blue light adjustment with a wearable display system are provided. Embodiments of the systems and methods for blue light adjustment can include receiving an eye image of an eye exposed to an adjusted level of blue light; detecting a change in a pupillary response by comparison of the received eye image to a first image; determining that the pupillary response corresponds to a biometric characteristic of a human individual; and allowing access to a biometric application based on the pupillary response determination.

    PERIOCULAR TEST FOR MIXED REALITY CALIBRATION
    115.
    发明申请

    公开(公告)号:US20200250872A1

    公开(公告)日:2020-08-06

    申请号:US16780698

    申请日:2020-02-03

    Abstract: A wearable device can include an inward-facing imaging system configured to acquire images of a user's periocular region. The wearable device can determine a relative position between the wearable device and the user's face based on the images acquired by the inward-facing imaging system. The relative position may be used to determine whether the user is wearing the wearable device, whether the wearable device fits the user, or whether an adjustment to a rendering location of virtual object should be made to compensate for a deviation of the wearable device from its normal resting position.

    PERIOCULAR AND AUDIO SYNTHESIS OF A FULL FACE IMAGE

    公开(公告)号:US20200226830A1

    公开(公告)日:2020-07-16

    申请号:US16721625

    申请日:2019-12-19

    Inventor: Adrian Kaehler

    Abstract: Systems and methods for synthesizing an image of the face by a head-mounted device (HMD) are disclosed. The HMD may not be able to observe a portion of the face. The systems and methods described herein can generate a mapping from a conformation of the portion of the face that is not imaged to a conformation of the portion of the face observed. The HMD can receive an image of a portion of the face and use the mapping to determine a conformation of the portion of the face that is not observed. The HMD can combine the observed and unobserved portions to synthesize a full face image.

    Blue light adjustment for biometric security

    公开(公告)号:US10664582B2

    公开(公告)日:2020-05-26

    申请号:US16170915

    申请日:2018-10-25

    Inventor: Adrian Kaehler

    Abstract: Systems and methods for blue light adjustment with a wearable display system are provided. Embodiments of the systems and methods for blue light adjustment can include receiving an eye image of an eye exposed to an adjusted level of blue light; detecting a change in a pupillary response by comparison of the received eye image to a first image; determining that the pupillary response corresponds to a biometric characteristic of a human individual; and allowing access to a biometric application based on the pupillary response determination.

    NEURAL NETWORK FOR EYE IMAGE SEGMENTATION AND IMAGE QUALITY ESTIMATION

    公开(公告)号:US20200005462A1

    公开(公告)日:2020-01-02

    申请号:US16570418

    申请日:2019-09-13

    Abstract: Systems and methods for eye image segmentation and image quality estimation are disclosed. In one aspect, after receiving an eye image, a device such as an augmented reality device can process the eye image using a convolutional neural network with a merged architecture to generate both a segmented eye image and a quality estimation of the eye image. The segmented eye image can include a background region, a sclera region, an iris region, or a pupil region. In another aspect, a convolutional neural network with a merged architecture can be trained for eye image segmentation and image quality estimation. In yet another aspect, the device can use the segmented eye image to determine eye contours such as a pupil contour and an iris contour. The device can use the eye contours to create a polar image of the iris region for computing an iris code or biometric authentication.

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