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:
Oct. 14, 2025

Filed:

Sep. 01, 2023
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Valentin Bazarevsky, San Jose, CA (US);

Fan Zhang, Sunnyvale, CA (US);

Andrei Tkachenka, Mountain View, CA (US);

Andrei Vakunov, Mountain View, CA (US);

Matthias Grundmann, San Jose, CA (US);

Assignee:

GOOGLE LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/246 (2017.01); G06T 7/73 (2017.01); G06V 40/20 (2022.01);
U.S. Cl.
CPC ...
G06T 7/251 (2017.01); G06T 7/75 (2017.01); G06V 40/28 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/30196 (2013.01);
Abstract

Example aspects of the present disclosure are directed to computing systems and methods for hand tracking using a machine-learned system for palm detection and key-point localization of hand landmarks. In particular, example aspects of the present disclosure are directed to a multi-model hand tracking system that performs both palm detection and hand landmark detection. Given a sequence of image frames, for example, the hand tracking system can detect one or more palms depicted in each image frame. For each palm detected within an image frame, the machine-learned system can determine a plurality of hand landmark positions of a hand associated with the palm. The system can perform key-point localization to determine precise three-dimensional coordinates for the hand landmark positions. In this manner, the machine-learned system can accurately track a hand depicted in the sequence of images using the precise three-dimensional coordinates for the hand landmark positions.


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