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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.

Patent No.:

US 11334765 B1

PDFFull Text
Date of Patent:
May. 17, 2022

Filed:

Jan. 13, 2021

Training a neural network with representations of user interface devices

Applicant:

Magic Leap, Inc., Plantation, FL (US);

Inventors:

Adrian Kaehler, Los Angeles, CA (US);

Gary R. Bradski, Plantation, FL (US);

Vijay Badrinarayanan, Mountain View, CA (US);

Assignee:

Magic Leap, Inc., Plantation, FL (US);

Attorney:

Knobbe, Martens, Olson & Bear, LLP

Primary Examiner:

Antonio A Caschera

Int. Cl.
CPC ...
G06F 3/01 (2006.01); G06K 9/62 (2022.01); G06N 3/04 (2006.01); G06N 3/10 (2006.01); G06K 9/00 (2022.01); G06V 20/10 (2022.01); G06V 20/20 (2022.01); G06V 40/20 (2022.01); G06T 7/70 (2017.01); G06F 3/0346 (2013.01); G06F 3/04815 (2022.01); G06N 3/08 (2006.01); G06T 19/00 (2011.01); G06N 7/00 (2006.01); G06N 5/02 (2006.01); G06N 5/00 (2006.01); G06V 10/44 (2022.01);
U.S. Cl.
CPC ...
G06K 9/6257 (2013.01); G06F 3/011 (2013.01); G06F 3/017 (2013.01); G06F 3/0346 (2013.01); G06F 3/04815 (2013.01); G06K 9/00 (2013.01); G06N 3/0445 (2013.01); G06N 3/0454 (2013.01); G06N 3/0481 (2013.01); G06N 3/08 (2013.01); G06N 3/105 (2013.01); G06T 7/70 (2017.01); G06T 19/006 (2013.01); G06V 20/10 (2022.01); G06V 20/20 (2022.01); G06V 40/28 (2022.01); G06F 2203/04804 (2013.01); G06F 2203/04807 (2013.01); G06N 3/0472 (2013.01); G06N 5/003 (2013.01); G06N 5/025 (2013.01); G06N 7/005 (2013.01); G06T 2207/10012 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06V 10/454 (2022.01);
Abstract

A wearable display system can be capable of determining a user interface (UI) event with respect to a virtual UI device (e.g., a button) and a pointer (e.g., a finger or a stylus) using a neural network. The wearable display system can render a representation of the UI device onto an image of the pointer captured when the virtual UI device is shown to the user and the user uses the pointer to interact with the virtual UI device. The representation of the UI device can include concentric shapes (or shapes with similar or the same centers of gravity) of high contrast. The neural network can be trained using training images with representations of virtual UI devices and pointers.

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