Obtaining high-resolution oculometric parameters

A non-transitory computer-readable medium having instructions that, when executed by a computer, cause the computer to execute a method, the method comprising:

• obtaining a video stream from a client device associated with a user, the video stream including a video of a face of the user;
• providing as input the video stream to a first prediction model to obtain a first set of oculometric parameters of an eye of the user, the first set of oculometric parameters including first iris data or first eyelid data;
• deconvolving the video stream based on the first eyelid data, stimulus data, or environment data to obtain adjusted eyelid data as part of the first set of oculometric parameters, the stimulus data including spatio-temporal information or optical information of a video stimulus presented on a display associated with the client device, the environment data including light conditions in an environment the client device is in;
• and
• providing as input the first set of oculometric parameters to a second prediction model to obtain a second set of oculometric parameters at a greater resolution than the first set of oculometric parameters, wherein the second set of oculometric parameters includes an iris radius, an iris translation, or an iris rotation.

A system, comprising:

• one or more memories;
• and
• at least one processor each coupled to at least one of the memories and configured to perform operations comprising:
• obtaining a video stream from a client device associated with a user, the video stream including a video of a face of the user;
• providing as input the video stream to a first prediction model to obtain a first set of oculometric parameters of an eye of the user, the first set of oculometric parameters including first iris data or first eyelid data, wherein the first set of oculometric parameters are obtained at a first resolution;
• deconvolving the video stream based on the first eyelid data, stimulus data or environment data to obtain adjusted eyelid data as part of the first set of oculometric parameters, the stimulus data including spatio-temporal information or optical information of a video stimulus presented on a display associated with the client device, the environment data including light conditions in an environment the client device is in;
• and
• providing as input the first set of oculometric parameters to a second prediction model to obtain a second set of oculometric parameters at a second resolution, wherein the second set of oculometric parameters includes second iris data including an iris radius, an iris translation, or an iris rotation, and wherein the second resolution is greater than the first resolution.