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:
Aug. 10, 2021

Filed:

May. 23, 2019
Applicant:

Avodah Labs, Inc., Arlington, TX (US);

Inventors:

Trevor Chandler, Thornton, CO (US);

Dallas Nash, Frisco, TX (US);

Michael Menefee, Richardson, TX (US);

Assignee:

AVODAH, INC., Wilmington, DE (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/73 (2017.01); G06F 3/01 (2006.01); G06K 9/00 (2006.01); G06T 7/20 (2017.01); G06N 3/04 (2006.01); G06F 3/03 (2006.01);
U.S. Cl.
CPC ...
G06T 7/73 (2017.01); G06F 3/017 (2013.01); G06F 3/0304 (2013.01); G06K 9/00248 (2013.01); G06K 9/00342 (2013.01); G06K 9/00355 (2013.01); G06N 3/0454 (2013.01); G06T 7/20 (2013.01);
Abstract

Disclosed are methods, apparatus and systems for gesture recognition based on neural network processing. One exemplary method for identifying a gesture communicated by a subject includes receiving a plurality of images associated with the gesture, providing the plurality of images to a first 3-dimensional convolutional neural network (3D CNN) and a second 3D CNN, where the first 3D CNN is operable to produce motion information, where the second 3D CNN is operable to produce pose and color information, and where the first 3D CNN is operable to implement an optical flow algorithm to detect the gesture, fusing the motion information and the pose and color information to produce an identification of the gesture, and determining whether the identification corresponds to a singular gesture across the plurality of images using a recurrent neural network that comprises one or more long short-term memory units.


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