Dynamic scheduling and channel creation based on real-time or near-real-time content context analysis

• US 10,425,700 B2
• Filed: 12/31/2016
• Issued: 09/24/2019
• Est. Priority Date: 12/31/2016
• Status: Active Grant

• Current Assignee: Turner Broadcasting System Incorporated (Warner Bros. Discovery, Inc.)
• Original Assignee: Turner Broadcasting System Incorporated (Warner Bros. Discovery, Inc.)
• Inventors: Loheide, Donald Jude, Monteiro, Carlos Jorge M, Webb, Nicolas Paul, Pope, V, Mark Cooper, Arnzen, James J
• Primary Examiner(s): Shang, Annan Q
• Application Number:
  US15/396,453
• Publication Number:
  US 20180192164A1
• Time in Patent Office: 997 Days
• Field of Search: 725 32- 36, 709217-232
• CPC Class Codes: H04N 21/2187 Live feed
• CPC Class Codes: H04N 21/23424 involving splicing one content stream with another content stream, e.g. for inserting or substituting an advertisement
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/26283 for associating distribution time parameters to content, e.g. to generate electronic program guide data
• CPC Class Codes: H04N 21/2668 Creating a channel for a dedicated end-user group, e.g. insertion of targeted commercials based on end-user profiles information retrieval from the Internet by querying with filtering and personalisation G06F16/9535; arrangements for replacing or switching information during the broadcast H04H20/10; push services over packet-switching network H04L12/1859; adaptation of message content in packet-switching networks H04L51/063
• CPC Class Codes: H04N 21/4884 for displaying subtitles
• CPC Class Codes: H04N 21/8455 involving pointers to the content, e.g. pointers to the I-frames of the video stream

Abstract

A hardware media content packaging and distribution system that handles distribution of one or more channels to be viewed on one or more of a plurality of consumer devices, receives a media feed and a first programming schedule of a first channel of the one or more channels from a source device. Instructions are received from a programming service and/or a user-preference is received from a first consumer device of the plurality of consumer devices on which the first channel is viewed. Based on content context analysis, one or more other live feeds of other channels of the one or more channels or pre-encoded media assets, are analyzed. Based on the content context analysis, a media item is recommended to be inserted in the media feed of the first channel, based on the received user-preference. The recommended media item is dynamically scheduled in the media feed of the first channel to be delivered over a distribution system to be viewed on the first consumer device based on the content context analysis.

Claims

1. A media content packaging and distribution system, comprising:

one or more processors configured to;

handle distribution of a plurality of channels that are viewed on at least one consumer device of a plurality of consumer devices;

receive a media feed and a first programming schedule of a first channel of the plurality of channels from a source device;

receive a user-preference from a first consumer device of the plurality of consumer devices, wherein the first channel is viewed on the first consumer device;

analyze, based on content context analysis, at least one live feed of a second channel of the plurality of channels or one or more pre-encoded media assets;

recommend a media item for insertion in the media feed of the first channel, wherein the media item is recommended based on;

the received user-preference, and

the content context analysis;

detect an upcoming inbound trigger in the received media feed after the recommendation of the media item;

determine a point of insertion of the recommended media item in the received media feed of the first channel based on the upcoming inbound trigger; and

dynamically schedule the recommended media item in the media feed of the first channel based on the content context analysis and the point of insertion,

wherein the recommended media item is delivered over a network.

2. The media content packaging and distribution system according to claim 1, wherein the one or more processors are further configured to execute the content context analysis in real time or near-real time.

3. The media content packaging and distribution system according to claim 1,

wherein the one or more processors are further configured to parse closed captions or subtitles for the content context analysis, and

wherein the closed captions or the subtitles are associated with the at least one live feed or the one or more pre-encoded media assets.

4. The media content packaging and distribution system according to claim 1,

wherein the one or more processors are further configured to parse in-stream program metadata or externally referenced metadata for the content context analysis, and

wherein the in-stream program metadata or the externally referenced metadata is associated with the at least one live feed.

5. The media content packaging and distribution system according to claim 1, wherein the one or more processors are further configured to utilize usage history, session history, previous decision results, pre-stored metadata, and historical data for the content context analysis.

6. The media content packaging and distribution system according to claim 1, wherein the content context analysis corresponds to content recognition-based detection of the media item from the at least one live feed of the second channel or the one or more pre-encoded media assets.

7. The media content packaging and distribution system according to claim 1,

wherein the one or more processors are further configured to generate a second programming schedule to deliver the recommended media item over the network, and

wherein the second programming schedule is based on the first programming schedule.

8. The media content packaging and distribution system according to claim 7, wherein the one or more processors are further configured to create a third channel from the first channel based on the received user-preference, the content context analysis, and the generated second programming schedule.

9. The media content packaging and distribution system according to claim 7,

wherein the one or more processors are further configured to retain a programming history, decision results, and metadata for use in future programming decisions, recommendations, and analysis, and

wherein the programming history corresponds to the generated second programming schedule.

10. The media content packaging and distribution system according to claim 1, wherein the one or more processors are further configured to:

modify the first programming schedule based on the upcoming inbound trigger;

generate a plurality of programming schedules based on the modification of the first programming schedule; and

dynamically create a plurality of new channels from the first channel based on;

the user-preference received from the first consumer device,

the content context analysis, and

the plurality of programming schedules.

11. The media content packaging and distribution system according to claim 1, wherein the one or more processors are further configured to:

modify the first programming schedule based on the upcoming inbound trigger;

generate a plurality of programming schedules based on the modification of the first programming schedule; and

dynamically alter programming for the first channel based on;

the user-preference received from the first consumer device,

the content context analysis, and

the plurality of programming schedules.

12. The media content packaging and distribution system according to claim 1, wherein the one or more processors are further configured to:

modify the first programming schedule based on the upcoming inbound trigger;

generate a plurality of programming schedules for the plurality of consumer devices based on the modification of the first programming schedule; and

create a plurality of new channels from the first channel based on;

a plurality of user-preferences received from the plurality of consumer devices,

content context analysis based on the received plurality of user-preferences, and

the plurality of programming schedules.

13. The media content packaging and distribution system according to claim 1,

wherein the one or more processors are further configured to communicate a notification of the recommended media item to the first consumer device,

wherein the notification seeks a confirmation from a user of the first consumer device to display the recommended media item on the first consumer device,

wherein the dynamic scheduling and delivery of the recommended media item is further based on the confirmation from the first consumer device.

14. The media content packaging and distribution system according to claim 13, wherein the dynamic scheduling and the delivery of the recommended media item is further based on an aggregation of votes or user-preferences from the plurality of consumer devices.

15. The media content packaging and distribution system according to claim 13,

wherein the one or more processors are further configured to receive the confirmation to display the recommended media item from the user of the first consumer device, and

wherein the recommended media item is scheduled in the received media feed of the first channel based on the received confirmation.

16. The media content packaging and distribution system according to claim 1, wherein the one or more processors are further configured to:

stitch a plurality of media items in at least one spot of the received media feed, wherein the plurality of media items corresponds to the recommended media item that is scheduled; and

generate a program stream based on the stitched plurality of media items, wherein the program stream is for distribution to the plurality of consumer devices.

17. The media content packaging and distribution system according to claim 1, wherein the one or more processors are further configured to:

detect a real-time event or a near real-time event in the at least one live feed of the second channel based on the content context analysis; and

recommend the media item based on the real-time event or the near real-time event, wherein the recommended media item is for insertion in a spot of the received media feed.

18. A method, comprising:

in a media content packaging and distribution system that is configured to handle distribution of a plurality of channels that are viewed on at least one consumer device of a plurality of consumer devices;

receiving a media feed and a first programming schedule of a first channel of the plurality of channels from a source device;

receiving a user-preference from a first consumer device of the plurality of consumer devices, wherein the first channel is viewed on the first consumer device;

analyzing, based on content context analysis, at least one live feed of a second channel of the plurality of channels or one or more pre-encoded media assets;

recommending a media item for insertion in the media feed of the first channel, wherein the media item is recommended based on;

the received user-preference, and

the content context analysis;

detecting an upcoming inbound trigger in the received media feed after the recommendation of the media item;

determining a point of insertion of the recommended media item in the received media feed of the first channel based on the upcoming inbound trigger; and

dynamically scheduling the recommended media item in the media feed of the first channel based on the content context analysis and the point of insertion,

wherein the recommended media item is delivered over a network.

19. The method according to claim 18, further comprising:

executing the content context analysis in real time or near-real time.

20. The method according to claim 18, further comprising:

parsing closed captions or subtitles for the content context analysis,

wherein the closed captions or the subtitles are associated with the at least one live feed or the one or more pre-encoded media assets.

21. The method according to claim 18, further comprising:

parsing in-stream program metadata or externally referenced metadata for the content context analysis,

wherein the in-stream program metadata or the externally referenced metadata is associated with the at least one live feed.

22. The method according to claim 18, further comprising:

utilizing usage history, session history, previous decision results, pre-stored metadata, and historical data for the content context analysis.

23. The method according to claim 18, wherein the content context analysis corresponds to content recognition-based detection of the media item from the at least one live feed of the second channel or the one or more pre-encoded media assets.

24. The method according to claim 18, further comprising:

modifying the first programming schedule to generate a second programming schedule,

wherein the second programming schedule is generated to deliver the recommended media item over the network.

25. The method according to claim 24, further comprising:

creating a third channel from the first channel based on the received user-preference, the content context analysis, and the generated second programming schedule.

26. The method according to claim 24, further comprising:

retaining a programming history, decision results, and metadata for use in future programming decisions, recommendations, and analysis,

wherein the programming history corresponds to the generated second programming schedule.

27. The method according to claim 18, further comprising:

modifying the first programming schedule based on the upcoming inbound trigger;

generating a plurality of programming schedules based on the modification of the first programming schedule; and

dynamically creating a plurality of new channels from the first channel based on;

the user-preference,

the content context analysis, and

the plurality of programming schedules.

28. The method according to claim 18, further comprising:

modifying the first programming schedule based on the upcoming inbound trigger;

generating a plurality of programming schedules based on the modification of the first programming schedule; and

dynamically altering programming for the first channel based on;

the user-preference received from the first consumer device,

the content context analysis, and

the plurality of programming schedules.

29. The method according to claim 18, further comprising:

modifying the first programming schedule based on the upcoming inbound trigger;

generating a plurality of programming schedules for the plurality of consumer devices based on the modification of the first programming schedule; and

creating a plurality of new channels from the first channel based on;

a plurality of user-preferences received from the plurality of consumer devices,

content context analysis based on the received plurality of user-preferences, and

the plurality of programming schedules.

30. The method according to claim 18, further comprising:

communicating a notification of the recommended media item to the first consumer device,

wherein the notification seeks a confirmation from a user of the first consumer device to display the recommended media item on the first consumer device,

wherein the dynamic scheduling and delivery of the recommended media item is further based on the confirmation from the first consumer device.

31. The method according to claim 30, wherein the dynamic scheduling and the delivery of the recommended media item is further based on an aggregation of votes or user-preferences from the plurality of consumer devices.

32. The method according to claim 30, further comprising:

receiving the confirmation to display the recommended media item from the user of the first consumer device,

wherein the recommended media item is scheduled in the received media feed of the first channel based on the received confirmation.

33. The method according to claim 18, further comprising:

stitching a plurality of media items in at least one spot of the received media feed, wherein the plurality of media items corresponds to the recommended media item that is scheduled; and

generating a program stream based on the stitched plurality of media items, wherein the program stream is for distribution to the plurality of consumer devices.

34. The method according to claim 18, further comprising:

detecting a real-time event or a near real-time event in the at least one live feed of second channel based on the content context analysis; and

recommending the media item based on the real-time event or the near real-time event, wherein the recommended media item is for insertion in a spot of the received media feed.

35. A non-transitory computer-readable medium having stored thereon, computer implemented instructions that when executed by a computer, cause the computer to execute operations, the operations comprising:

in a media content packaging and distribution system that is configured to handle distribution of a plurality of channels that are viewed on at least one consumer device of a plurality of consumer devices;

receiving a media feed and a first programming schedule of a first channel of the plurality of channels from a source device;

receiving a user-preference from a first consumer device of the plurality of consumer devices, wherein the first channel is viewed on the first consumer device;

analyzing, based on content context analysis, at least one live feed of a second channel of the plurality of channels or one or more pre-encoded media assets;

recommending a media item for insertion in the media feed of the first channel, wherein the media item is recommended based on;

the received user-preference, and

the content context analysis;

detecting an upcoming inbound trigger in the received media feed after the recommendation of the media item;

determining a point of insertion of the recommended media item in the received media feed of the first channel based on the upcoming inbound trigger; and

dynamically scheduling the recommended media item in the media feed of the first channel based on the content context analysis and the point of insertion,

wherein the recommended media item is delivered over a network.