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:
Jun. 06, 2023

Filed:

Aug. 28, 2020
Applicant:

Pxl Vision Ag, Zurich, CH;

Inventors:

Mikhail Vorobiev, Zurich, CH;

Nevena Shamoska, Zürich, CH;

Magdalena Polac, Zürich, CH;

Benjamin Fankhauser, Biel-Bienne, CH;

Michael Goettlicher, Biel-Bienne, CH;

Marcus Hudritsch, Biel-Bienne, CH;

Suman Saha, Zurich, CH;

Stamatios Georgoulis, Zurich, CH;

Luc van Gool, Zurich, CH;

Assignee:

PXL Vision AG, Zurich, CH;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 40/00 (2022.01); G06V 40/40 (2022.01); B42D 25/23 (2014.01); B42D 25/328 (2014.01); G06N 3/08 (2023.01); G06V 10/25 (2022.01); G06V 10/75 (2022.01); G06V 30/413 (2022.01); G06V 40/60 (2022.01); G06V 40/16 (2022.01); G06F 18/214 (2023.01);
U.S. Cl.
CPC ...
G06V 40/45 (2022.01); B42D 25/23 (2014.10); B42D 25/328 (2014.10); G06F 18/214 (2023.01); G06N 3/08 (2013.01); G06V 10/25 (2022.01); G06V 10/751 (2022.01); G06V 30/413 (2022.01); G06V 40/168 (2022.01); G06V 40/172 (2022.01); G06V 40/67 (2022.01);
Abstract

A system for remote identification of users. The system uses deep learning techniques for authenticating a user from an identification document and using automated verification of identification documents. Identification documents may be authenticated by validating security features. The system may determine features expected in a valid identification document and determine whether those features are present, employing techniques, such as determining whether direction-sensitive features are present. Liveness of a user indicated by the identification document may be determined with a deep learning model trained for identification of facial spoofing attacks.


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