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. 17, 2024

Filed:

May. 17, 2021
Applicant:

Tencent Technology (Shenzhen) Company Limited, Shenzhen, CN;

Inventors:

Xing Ji, Shenzhen, CN;

Yitong Wang, Shenzhen, CN;

Zheng Zhou, Shenzhen, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06F 18/214 (2023.01); G06N 3/08 (2023.01); G06V 10/44 (2022.01); G06V 10/75 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 40/16 (2022.01);
U.S. Cl.
CPC ...
G06V 40/176 (2022.01); G06F 18/214 (2023.01); G06N 3/08 (2013.01); G06V 10/454 (2022.01); G06V 10/751 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 40/171 (2022.01); G06V 40/172 (2022.01);
Abstract

An electronic device obtains an image that includes a face. The device performs feature extraction on the image, to obtain facial expression information corresponding to the face and facial feature information corresponding to the facial expression, wherein the facial feature information indicates an extent of the facial expression. The device determines facial emotion information according to the facial expression information. The device also determines facial feature expression information according to a target feature value corresponding to the facial emotion and the facial feature information. This expression recognition techniques disclosed herein can implement multi-task learning and reduce an amount of data required for model training, and can obtain both an emotion recognition result and a local expression recognition result, thereby improving efficiency and real-time performance of expression recognition and improving user experience.


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