Deep neural network for iris identification

A system for training a deep neural network for iris authentication, comprising:

• computer-readable memory storing executable instructions;
• and
• one or more hardware-based hardware processors programmed by the executable instructions to at least:
• access a deep neural network comprising a plurality of layers, wherein each layer of the plurality of layers is connected to at least another layer of the plurality of layers;
• provide the deep neural network with a training set comprising eye images of a plurality of persons;
• compute embedding space representations of the plurality of eye images using the deep neural network, wherein the embedding space representations of the plurality of eye images of the same person are within a threshold;
• and
• update the deep neural network based on the distances between the embedding space representations of eye images of the same persons and different persons.

A head mounted display system comprising:

• a display;
• an image capture device configured to capture a first image of an eye of a user;
• non-transitory memory configured to store executable instructions;
• and
• a hardware processor in communication with the display, the image capture device, and the non-transitory memory, the hardware processor programmed by the executable instructions to:
• receive the first image of the eye;
• process the first image of the eye to generate a representation of the first image of the eye in polar coordinates;
• process the representation of the first image of the eye in polar coordinates using a deep neural network to generate an embedding space representation;
• and
• process the embedding space representation using a classifier to generate a likelihood score that the image of the eye is an image of the authorized user's eye.