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:
Sep. 10, 2024

Filed:

May. 01, 2023
Applicant:

Nuralogix Corporation, Toronto, CA;

Inventors:

Kang Lee, Toronto, CA;

Evgueni Kabakov, North York, CA;

Winston De Armas, Hamilton, CA;

Alan Ding, North Vancouver, CA;

Darshan Singh Panesar, Toronto, CA;

Assignee:

NURALOGIX CORPORATION, Toronto, CA;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G16H 10/60 (2018.01); A61B 5/00 (2006.01); A61B 5/026 (2006.01); G06N 20/00 (2019.01); G06V 10/42 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/00 (2022.01); G06V 40/16 (2022.01); G06V 40/40 (2022.01); G16H 30/40 (2018.01); G06V 40/10 (2022.01);
U.S. Cl.
CPC ...
G16H 10/60 (2018.01); A61B 5/0261 (2013.01); A61B 5/7267 (2013.01); G06N 20/00 (2019.01); G06V 10/431 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/95 (2022.01); G06V 40/161 (2022.01); G06V 40/172 (2022.01); G06V 40/40 (2022.01); G16H 30/40 (2018.01); G06V 40/15 (2022.01);
Abstract

A system and method for detection of synthesized videos of humans. The method including: determining blood flow signals using a first machine learning model trained with a hemoglobin concentration (HC) changes training set, the first machine learning model taking as input bit values from a set of bitplanes in a captured image sequence, the HC changes training set including bit values from each bitplane of images captured from a set of subjects for which HC changes are known; determining whether blood flow patterns from the video are indicative of a synthesized video using a second machine learning model, the second machine learning model taking as input the blood flow signals, the second machine learning model trained using a blood flow training set including blood flow data signals from at least one of a plurality of videos of other human subjects for which it is known whether each video is synthesized.


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