The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 29, 2025

Filed:

Sep. 04, 2024
Applicant:

Neuralight Ltd., Tel Aviv, IL;

Inventors:

Edmund Ben-Ami, Tel Aviv, IL;

Micha Yochanan Breakstone, Austin, TX (US);

Rotem Zvi Bar-Or, Boulder, CO (US);

Vladimir Anisimov, Tel-Aviv, IL;

Assignee:

NeuraLight, Ltd., Tel Aviv, IL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/04 (2022.12); A61B 3/00 (2005.12); A61B 3/113 (2005.12); A61B 5/16 (2005.12); G06F 3/01 (2005.12); G06N 3/084 (2022.12); G06N 3/09 (2022.12); G06T 7/00 (2016.12); G06T 7/246 (2016.12); G06V 10/82 (2021.12); G06V 40/18 (2021.12);
U.S. Cl.
CPC ...
G06V 40/18 (2021.12); A61B 3/0025 (2012.12); A61B 3/113 (2012.12); A61B 5/163 (2017.07); G06F 3/013 (2012.12); G06T 7/0012 (2012.12); G06T 2207/20081 (2012.12); G06T 2207/30041 (2012.12);
Abstract

Disclosed are systems and methods for extracting high resolution oculometric parameters. A video stream having a video of a face of a user is processed to obtain a set of oculometric parameters, such as eyelid data, iris data (e.g., iris translation, iris radius and iris rotation), and pupil data (e.g., pupil center and pupil radius) at a first resolution. A deconvolution process is performed on the video stream to improve accuracy or resolution of the oculometric parameters, based on stimulus information of a video stimulus displayed on a client device associated with the user, environment data of an environment in which the user is located, device data of the client device, etc. The oculometric parameters are then processed using a prediction model that is trained based on high resolution oculometric parameters obtained using eye tracking devices to predict oculometric parameters at a resolution greater than the first resolution.


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