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:
Jul. 11, 2017

Filed:

Jun. 16, 2015
Applicant:

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

Inventors:

Anirudh Koul, Sunnyvale, CA (US);

Serge-Eric Tremblay, San Jose, CA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); H04N 21/4722 (2011.01); G06K 9/62 (2006.01); H04N 21/2187 (2011.01); H04N 21/234 (2011.01); H04N 21/8405 (2011.01);
U.S. Cl.
CPC ...
G06K 9/00221 (2013.01); G06K 9/00 (2013.01); G06K 9/00711 (2013.01); G06K 9/6269 (2013.01); H04N 21/2187 (2013.01); H04N 21/23418 (2013.01); H04N 21/4722 (2013.01); H04N 21/8405 (2013.01);
Abstract

Architecture that enables the identification of entities such as people and content in live broadcasts (e.g., streaming content (e.g., video) of live events) and non-live presentations (e.g., movies), in realtime, using recognition processes. This can be accomplished by extracting live data related to a live event. With respect to people entities, filtering can be performed to identify the named (people) entities from the extracted live data, and trending topics discovered as relate to the named entities, as associated with the live event. Multiple images of the named entities that capture the named entities under different conditions are captured for the named entities. The images are then processed to extract and learn facial features (train one or more models), and facial recognition is then performed on faces in the video using the trained model(s).


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