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. 14, 2022

Filed:

Jul. 15, 2020
Applicant:

Roku, Inc., San Jose, CA (US);

Inventors:

Sunil Suresh Kulkarni, San Jose, CA (US);

Pradipkumar Dineshbhai Gajjar, Sunnyvale, CA (US);

Jose Pio Pereira, Cupertino, CA (US);

Preshant Ramanathan, Mountain View, CA (US);

Mihailo M. Stojancic, San Jose, CA (US);

Shashank Merchant, Sunnyvale, CA (US);

Assignee:

Roku, Inc., San Jose, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 16/45 (2019.01); G06F 16/48 (2019.01); G06F 16/906 (2019.01); G06F 16/44 (2019.01);
U.S. Cl.
CPC ...
G06F 16/45 (2019.01); G06F 16/48 (2019.01); G06F 16/44 (2019.01); G06F 16/906 (2019.01);
Abstract

Techniques are described that exclude use of 'stop-fingerprints' from media database formation and search query to an automatic content recognition (ACR) systems based on media content fingerprints updated by stop-fingerprint analysis. A classification process is presented which takes in fingerprints from reference media files as an input and produces a modified set of fingerprints as an output by applying a novel stop-fingerprint classification algorithm. Architecture for the distributed stop-fingerprint generation is presented. Various cases, as stop-fingerprints generation for the entire reference database, stop-fingerprints generation for the individual reference fingerprint files, and temporal fingerprint classification obtained through intermediate steps of the temporal fingerprint classification algorithm are presented. A hash-based signature classification algorithm is also described.


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