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:
Jul. 12, 2022

Filed:

May. 22, 2020
Applicant:

Samsung Electronics Co., Ltd., Suwon-si, KR;

Inventors:

Seon Min Rhee, Seoul, KR;

Jungbae Kim, Seoul, KR;

Byungin Yoo, Seoul, KR;

Jaejoon Han, Seoul, KR;

Seungju Han, Seoul, KR;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 40/16 (2022.01); G06K 9/62 (2022.01); G06T 15/04 (2011.01); G06T 19/20 (2011.01); G06V 10/32 (2022.01); G06V 20/64 (2022.01);
U.S. Cl.
CPC ...
G06V 40/169 (2022.01); G06K 9/627 (2013.01); G06K 9/6271 (2013.01); G06K 9/6296 (2013.01); G06T 15/04 (2013.01); G06T 19/20 (2013.01); G06V 10/32 (2022.01); G06V 20/647 (2022.01); G06V 40/165 (2022.01); G06V 40/172 (2022.01); G06T 2219/2021 (2013.01);
Abstract

Face recognition of a face, to determine whether the face correlates with an enrolled face, may include generating a personalized three-dimensional (3D) face model based on a two-dimensional (2D) input image of the face, acquiring 3D shape information and a normalized 2D input image of the face based on the personalized 3D face model, generating feature information based on the 3D shape information and pixel color values of the normalized 2D input image, and comparing the feature information with feature information associated with the enrolled face. The feature information may include first and second feature information generated based on applying first and second deep neural network models to the pixel color values of the normalized 2D input image and the 3D shape information, respectively. The personalized 3D face model may be generated based on transforming a generic 3D face model based on landmarks detected in the 2D input image.


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