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:
Dec. 24, 2024

Filed:

Feb. 25, 2022
Applicants:

Chongqing University, Chongqing, CN;

Star Institute of Intelligent Systems, Chongqing, CN;

Db (Chongqing) Intelligent Technology Research Institute Co., Ltd., Chongqing, CN;

Univeristy of Electronic Science and Technology of China, Chengdu, CN;

Inventors:

Yongduan Song, Chongqing, CN;

Feng Yang, Chengdu, CN;

Rui Li, Chongqing, CN;

Qin Chen, Chongqing, CN;

Shichun Wang, Chongqing, CN;

Hongyu Xia, Chongqing, CN;

Caishi He, Chongqing, CN;

Shihao Pu, Chongqing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/73 (2017.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 40/16 (2022.01); G06V 40/18 (2022.01);
U.S. Cl.
CPC ...
G06T 7/73 (2017.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G06V 40/171 (2022.01); G06V 40/18 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30201 (2013.01);
Abstract

Embodiments of the present disclosure provide a quantitative method and system for attention based on a line-of-sight estimation neural network, which improves the stability and training efficiency of the line-of-sight estimation neural network. A few-sample learning method is applied to training of the line-of-sight estimation neural network, which improves generalization performance of the line-of-sight estimation neural network. A nonlinear division method for small intervals of angles of the line of sight is provided, which reduces an estimation error of the line-of-sight estimation neural network. Eye opening and closing detection is added to avoid the line-of-sight estimation error caused by an eye closing state. A method for solving a landing point of the line of sight is provided, which has high environmental adaptability and can be quickly used in actual deployment.


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