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. 04, 2018

Filed:

Oct. 20, 2016
Applicant:

Disney Enterprises, Inc., Burbank, CA (US);

Inventors:

Martin Klaudiny, Edinburgh, GB;

Steven McDonagh, Edinburgh, GB;

Derek Bradley, Zürich, CH;

Thabo Beeler, Zürich, CH;

Iain Matthews, Pittsburgh, PA (US);

Kenneth Mitchell, Earlston, GB;

Assignee:

DISNEY ENTERPRISES, INC., Burbank, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06T 13/40 (2011.01); G06T 19/20 (2011.01); G06T 15/50 (2011.01); G06K 9/00 (2006.01); G06K 9/66 (2006.01); G06T 7/20 (2017.01);
U.S. Cl.
CPC ...
G06K 9/6256 (2013.01); G06K 9/00335 (2013.01); G06K 9/66 (2013.01); G06T 7/20 (2013.01); G06T 13/40 (2013.01); G06T 15/50 (2013.01); G06T 19/20 (2013.01); G06T 2200/08 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30201 (2013.01); G06T 2207/30244 (2013.01);
Abstract

Provided are methods, systems, and computer-readable medium for synthetically generating training data to be used to train a learning algorithm that is capable of generating computer-generated images of a subject from real images that include the subject. The training data can be generated using a facial rig by changing expressions, camera viewpoints, and illumination in the training data. The training data can then be used for tracking faces in a real-time video stream. In such examples, the training data can be tuned to expected environmental conditions and camera properties of the real-time video stream. Provided herein are also strategies to improve training set construction by analyzing which attributes of a computer-generated image (e.g., expression, viewpoint, and illumination) require denser sampling.


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