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. 26, 2023

Filed:

Jun. 28, 2023
Applicant:

Nanjing Silicon Intelligence Technology Co., Ltd., Jiangsu, CN;

Inventors:

Huapeng Sima, Jiangsu, CN;

Hao Jiang, Jiangsu, CN;

Hongwei Fan, Jiangsu, CN;

Qixun Qu, Jiangsu, CN;

Jintai Luan, Jiangsu, CN;

Jiabin Li, Jiangsu, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 40/20 (2022.01); G06V 10/77 (2022.01); G06V 10/764 (2022.01);
U.S. Cl.
CPC ...
G06V 40/23 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 2201/12 (2022.01);
Abstract

A model including an information extraction layer that obtains image information of a training object in a depth image; a pixel point positioning layer that performs position estimation on a three-dimensional coordinate of human-body key points, defines a body part of the training object as a body component, and calibrates a three-dimensional coordinate of all human-body key points corresponding to the body component; a feature extraction layer that extracts a key-point position feature, a body moving speed feature, and a key-point moving speed feature for action recognition; a vector dimensionality reduction layer that combines the key-point position feature, the body moving speed feature, and the key-point moving speed feature as a multidimensional feature vector, and performs dimensionality reduction on the multidimensional feature vector; and a feature vector classification layer that classifies the multidimensional feature vector that is performed with dimensionality reduction, to recognize a fitness action of the training object.


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