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:
Sep. 03, 2019

Filed:

Sep. 15, 2017
Applicant:

Snap Inc., Venice, CA (US);

Inventors:

Lidiia Bogdanovych, Los Angeles, CA (US);

William Brendel, Los Angeles, CA (US);

Samuel Edward Hare, Pacific Palisades, CA (US);

Fedir Poliakov, Marina Del Rey, CA (US);

Guohui Wang, Los Angeles, CA (US);

Xuehan Xiong, Los Angeles, CA (US);

Jianchao Yang, Venice, CA (US);

Linjie Yang, Los Angeles, CA (US);

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/11 (2017.01); G06K 9/62 (2006.01); G06K 9/74 (2006.01); G06T 7/194 (2017.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01); G06K 9/68 (2006.01); H04N 7/14 (2006.01); H04N 5/445 (2011.01); H04N 5/76 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6256 (2013.01); G06K 9/626 (2013.01); G06K 9/6807 (2013.01); G06K 9/74 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 7/11 (2017.01); G06T 7/194 (2017.01); G06T 2207/10016 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/20024 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30201 (2013.01); H04N 5/44504 (2013.01); H04N 5/76 (2013.01); H04N 7/141 (2013.01);
Abstract

A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can be assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.

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