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. 25, 2023

Filed:

Oct. 26, 2021
Applicant:

Ubtech Robotics Corp Ltd, Shenzhen, CN;

Inventors:

Hanliu Wang, Shenzhen, CN;

Jun Cheng, Shenzhen, CN;

Jianxin Pang, Shenzhen, CN;

Assignee:

UBTECH ROBOTICS CORP LTD, Shenzhen, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 40/16 (2022.01); G06F 18/214 (2023.01); G06V 10/141 (2022.01); G06V 10/94 (2022.01); G06V 10/24 (2022.01); G06N 3/04 (2023.01);
U.S. Cl.
CPC ...
G06F 18/2148 (2023.01); G06N 3/04 (2013.01); G06V 10/141 (2022.01); G06V 10/245 (2022.01); G06V 10/95 (2022.01); G06V 40/166 (2022.01); G06V 40/171 (2022.01);
Abstract

A backlight face recognition method, a terminal device using the same, and a computer readable storage medium are provided. The method includes: performing a face detection on each original face image in an original face image sample set to obtain a face frame corresponding to the original face image; capturing the corresponding original face images from the original face image sample set, and obtaining a new face image containing background pixels corresponding to the captured original face images from the original face image sample set; preprocessing all the obtained new face images to obtain a backlight sample set and a normal lighting sample set; and training a convolutional neural network using the backlight sample set and the normal lighting sample set until the convolutional neural network reaches a preset stopping condition. The trained convolutional neural network will improve the accuracy of face recognition in complex background and strong light.


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