IP Library Granted Patent US 12,047,624
Granted Patent B2
US 12,047,624 · App. 17/702,169 · Granted Jul 23, 2024

Systems and methods for generating new content segments based on object name identification

Inventors: Alan Waterman (Merced, CA); Sahir Nasir (San Jose, CA)
Assignee: Rovi Guides, Inc.
H04N21/252G06N3/08G06N20/00H04N21/26603H04N21/2668
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Quick Facts
Patent No.
US 12,047,624
App. No.
17/702,169
Granted
Jul 23, 2024
Kind
B2
Abstract

Systems and methods are disclosed herein for generating new content segments based on object name identification. A content segment may be received from a device and a content structure is generated based on the content segment. The content structure includes objects each having attributes. The system may search a contact database associated with the device to identify a matching entry of the contact database with a particular object. The comparison matches metadata of the matching entry with an attribute of the particular object. Upon matching, the first object is modified to include a name attribute based on the matching metadata of the matching entry. In response to receiving a request using the name of the particular object to create a new content segment, the system inserts the particular object into a new content structure and a new content segment is generated for display from the new content structure.

Claims (41)

1. A method comprising:

accessing a video comprising a plurality of segments, wherein the segments comprise depiction of a plurality of persons;

generating a new content segment that includes a selected person from the video comprising the plurality of persons, wherein the person is selected based on:

obtaining an attribute of an object from the video comprising the plurality of segments;

applying image recognition to select the selected person from the video comprising the plurality of persons;

comparing the selected person with a profile photograph on a social network; and

determining the match if the selected person matches the profile photograph, wherein the match between the selected person and the profile photograph is determined based on similar landmarks on the face of the selected person and the profile photograph;

transmitting the new content segment to a recipient identified based on metadata of a matching entry of a contact database, wherein transmitting the new content segment to the recipient comprises:

determining an electronic address of the recipient based on the metadata of the matching entry of the contact database;

determining a type of communication network associated with the determined electronic address; and

transmitting the new content segment to the recipient based on the electronic address on the determined communication network.

2. The method of claim 1 , wherein generating the new content segment that includes the selected person from the video comprising the plurality of persons further comprises:

deconstructing a content segment from the video comprising the plurality of segments, wherein the deconstruction deconstructs the content segment into a plurality of objects; and

selecting a person from the plurality of objects for generating the new content that includes the selected person.

3. The method of claim 2 , further comprising, using image recognition to identify a person in the deconstructed content segment.

4. The method of claim 3 , wherein the image recognition comprises a machine learning model to implement at least one of a neural network or parallel processing.

5. The method of claim 1 , wherein comparing the selected person with the profile photograph on the social network includes comparing the attribute of the selected person with the profile photograph on the social network.

6. The method of claim 1 , wherein the match between the selected person and the profile photograph is determined based on RGB (Red-Green-Blue) values of the selected person and the profile photograph.

7. The method of claim 1 , wherein the contact database is the social network.

8. The method of claim 1 , wherein the contact database is an email service.

9. A system comprising:

control circuitry configured to:

access a video comprising a plurality of segments, wherein the segments comprise depiction of a plurality of persons;

generate a new content segment that includes a selected person from the video comprising the plurality of persons, wherein the person is selected based on:

obtaining an attribute of an object from the video comprising the plurality of segments;

applying image recognition to select the selected person from the video comprising the plurality of persons;

comparing the selected person with a profile photograph on a social network; and

determining the match if the selected person matches the profile photograph, wherein the match between the selected person and the profile photograph is determined based on similar landmarks on the face of the selected person and the profile photograph;

transmit the new content segment to a recipient identified based on metadata of a matching entry of a contact database, wherein transmitting the new content segment to the recipient comprises:

determining an electronic address of the recipient based on the metadata of the matching entry of the contact database;

determining a type of communication network associated with the determined electronic address; and

transmitting the new content segment to the recipient based on the electronic address on the determined communication network.

10. The system of claim 9 , wherein generating the new content segment that includes the selected person from the video comprising the plurality of persons further comprises, the control circuitry configured to:

deconstruct a content segment from the video comprising the plurality of segments, wherein the deconstruction deconstructs the content segment into a plurality of objects; and

select a person from the plurality of objects for generating the new content that includes the selected person.

11. The system of claim 10 , further comprising, the control circuitry configured to use image recognition to identify a person in the deconstructed content segment.

12. The system of claim 11 , wherein the image recognition comprises a machine learning model to implement at least one of a neural network or parallel processing.

13. The system of claim 9 , wherein comparing the selected person with the profile photograph on the social network includes the control circuitry configured to compare the attribute of the selected person with the profile photograph on the social network.

14. The system of claim 9 , wherein the match between the selected person and the profile photograph is determined by the control circuitry based on RGB (Red-Green-Blue) values of the selected person and the profile photograph.

15. The system of claim 9 , wherein the contact database is the social network.

16. The system of claim 9 , wherein the contact database is an email service.

Assignments (3)
CHANGE OF NAME Recorded Oct 3, 2024
From: ROVI GUIDES, INC.
To: ADEIA GUIDES INC.
Reel/Frame 069106/0238 →
SECURITY INTEREST Recorded May 3, 2023
From: ADEIA GUIDES INC.; ADEIA IMAGING LLC; ADEIA MEDIA HOLDINGS LLC; ADEIA MEDIA SOLUTIONS INC.; ADEIA SEMICONDUCTOR ADVANCED TECHNOLOGIES INC.; ADEIA SEMICONDUCTOR BONDING TECHNOLOGIES INC.; ADEIA SEMICONDUCTOR INC.; ADEIA SEMICONDUCTOR SOLUTIONS LLC; ADEIA SEMICONDUCTOR TECHNOLOGIES LLC; ADEIA SOLUTIONS LLC
To: BANK OF AMERICA, N.A., AS COLLATERAL AGENT
Reel/Frame 063529/0272 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 23, 2022
From: WATERMAN, ALAN; NASIR, SAHIR
To: ROVI GUIDES, INC.
Reel/Frame 059377/0745 →
Continuity (2)
Continuation 16714418 · Dec 13, 2019
Related Publication 20220217430A1 · Jul 7, 2022