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:
Jun. 08, 2021

Filed:

Sep. 14, 2018
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Muhammad Zeeshan Zia, Kirkland, WA (US);

Emanuel Shalev, Sammamish, WA (US);

Jonathan C. Hanzelka, Kenmore, WA (US);

Harpreet S. Sawhney, Redmond, WA (US);

Pedro U. Escos, Seattle, WA (US);

Michael J. Ebstyne, Seattle, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06N 20/00 (2019.01); G06T 19/00 (2011.01);
U.S. Cl.
CPC ...
G06K 9/00671 (2013.01); G06K 9/00201 (2013.01); G06N 20/00 (2019.01); G06T 19/006 (2013.01);
Abstract

The disclosure herein describes training a machine learning model to recognize a real-world object based on generated virtual scene variations associated with a model of the real-world object. A digitized three-dimensional (3D) model representing the real-world object is obtained and a virtual scene is built around the 3D model. A plurality of virtual scene variations is generated by varying one or more characteristics. Each virtual scene variation is generated to include a label identifying the 3D model in the virtual scene variation. A machine learning model may be trained based on the plurality of virtual scene variations. The use of generated digital assets to train the machine learning model greatly decreases the time and cost requirements of creating training assets and provides training quality benefits based on the quantity and quality of variations that may be generated, as well as the completeness of information included in each generated digital asset.


Find Patent Forward Citations

Loading…