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:
Feb. 18, 2025

Filed:

Dec. 11, 2023
Applicant:

Ultrahaptics Ip Two Limited, Bristol, GB;

Inventors:

Jonathan Marsden, San Mateo, CA (US);

Raffi Bedikian, San Francisco, CA (US);

David Samuel Holz, San Francisco, CA (US);

Assignee:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 18/214 (2023.01); G06F 3/01 (2006.01); G06F 18/24 (2023.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06T 7/246 (2017.01); G06T 7/285 (2017.01); G06T 7/73 (2017.01); G06V 10/70 (2022.01); G06V 20/64 (2022.01); G06V 40/20 (2022.01);
U.S. Cl.
CPC ...
G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 7/248 (2017.01); G06T 7/285 (2017.01); G06T 7/74 (2017.01); G06V 10/70 (2022.01); G06V 20/64 (2022.01); G06V 40/28 (2022.01); G06F 3/011 (2013.01); G06F 3/017 (2013.01); G06T 2207/10021 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30196 (2013.01);
Abstract

The technology disclosed introduces two types of neural networks: 'master' or “generalists” networks and “expert” or “specialists” networks. Both, master networks and expert networks, are fully connected neural networks that take a feature vector of an input hand image and produce a prediction of the hand pose. Master networks and expert networks differ from each other based on the data on which they are trained. In particular, master networks are trained on the entire data set. In contrast, expert networks are trained only on a subset of the entire dataset. In regards to the hand poses, master networks are trained on the input image data representing all available hand poses comprising the training data (including both real and simulated hand images).


Find Patent Forward Citations

Loading…