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. 08, 2020

Filed:

Nov. 30, 2018
Applicant:

Snap Inc., Santa Monica, CA (US);

Inventors:

Yuncheng Li, Los Angeles, CA (US);

Linjie Luo, Los Angeles, CA (US);

Xuecheng Nie, Singapore, SG;

Ning Zhang, Los Angeles, CA (US);

Assignee:

Snap Inc., Santa Monica, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/246 (2017.01); G06T 7/73 (2017.01); G06K 9/00 (2006.01); H04L 29/06 (2006.01); G06F 3/0481 (2013.01); H04L 12/58 (2006.01);
U.S. Cl.
CPC ...
G06T 7/246 (2017.01); G06K 9/00744 (2013.01); G06T 7/73 (2017.01); G06F 3/04817 (2013.01); G06T 2200/24 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30196 (2013.01); H04L 51/04 (2013.01); H04L 67/42 (2013.01);
Abstract

Systems, devices, media and methods are presented for a human pose tracking framework. The human pose tracking framework may identify a message with video frames, generate, using a composite convolutional neural network, joint data representing joint locations of a human depicted in the video frames, the generating of the joint data by the composite convolutional neural network done by a deep convolutional neural network operating on one portion of the video frames, a shallow convolutional neural network operating on a another portion of the video frames, and tracking the joint locations using a one-shot learner neural network that is trained to track the joint locations based on a concatenation of feature maps and a convolutional pose machine. The human pose tracking framework may store, the joint locations, and cause presentation of a rendition of the joint locations on a user interface of a client device.


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