Method and system for aggregating video content

• US 10,325,143 B2
• Filed: 02/01/2018
• Issued: 06/18/2019
• Est. Priority Date: 08/03/2016
• Status: Active Grant

• Current Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Original Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Inventors: Begeja, Lee, Liu, Zhu, Mu, Yadong, Renger, Bernard S., Gibbon, David Crawford, Shahraray, Behzad, Gopalan, Raghuraman, Zavesky, Eric
• Primary Examiner(s): Grant, II, Jerome
• Application Number:
  US15/886,027
• Publication Number:
  US 20180157895A1
• Time in Patent Office: 502 Days
• Field of Search: 382118
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/30201 Face
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06V 20/35 Categorising the entire scene, e.g. birthday party or wedding scene
• CPC Class Codes: G06V 20/40 in video content extracting overlay text G06V20/62; video retrieval G06F16/70; processing of video elementary streams in video servers H04N21/234; processing of video elementary streams in video clients H04N21/44
• CPC Class Codes: G06V 20/44 Event detection
• CPC Class Codes: G06V 20/52 Surveillance or monitoring of activities, e.g. for recognising suspicious objects recognising microscopic objects G06V20/69
• CPC Class Codes: G06V 40/16 Human faces, e.g. facial parts, sketches or expressions
• CPC Class Codes: G06V 40/172 Classification, e.g. identification
• CPC Class Codes: G11B 27/028 with computer assistance
• CPC Class Codes: G11B 27/031 Electronic editing of digitised analogue information signals, e.g. audio or video signals
• CPC Class Codes: H04N 7/181 for receiving images from a plurality of remote sources

Abstract

Aspects of the subject disclosure may include, for example, systems and methods aggregating video content and adjusting the aggregate video content according to a training model. The adjusted aggregate video content comprises a first subset of the images and does not comprise a second subset of the images. The first subset of the images is determined by the training model based on a plurality of categories corresponding to a plurality of events. The illustrative embodiments also include presenting the adjusted aggregate video content and receiving identifications for the first subset of the images in the aggregate video content. Further, the illustrative embodiments include adjusting the training model according to the identifications and providing the adjusted training model to a network device. Other embodiments are disclosed.

Claims

1. A device, comprising:

a processing system including a processor; and

a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, comprising;

aggregating video content from a plurality of cameras associated with a premises to generate aggregated video content for the premises, wherein the video content includes images of a plurality of events observed by the plurality of cameras;

analyzing the aggregated video content according to a training model to generate adjusted aggregated video content including a first subset of images while excluding a second subset of the images, wherein the first subset of images is determined by the training model based on a plurality of characteristics for the premises;

presenting the adjusted aggregated video content including the first subset of images;

receiving user-generated input for the adjusted aggregated video content, wherein the user-generated input provides identifications for the first subset of the images in the aggregated video content as the plurality of characteristics for the premises; and

adjusting the training model according to the user-generated input resulting in an adjusted training model.

2. The device of claim 1, wherein the plurality of characteristics for the premises includes neighborhood events, neighborhood information, neighbor information, and delivery event information.

3. The device of claim 1, wherein the second subset of the images is determined by the training model based on the plurality of characteristics for the premises.

4. The device of claim 1, wherein the operations further

comprise providing the adjusted training model to a network, and wherein the analyzing the aggregated video content further comprising applying the adjusted training model to the aggregated video content.

5. The device of claim 4, wherein the operations further comprise:

receiving a plurality of selectable training models from the network, wherein one of the plurality of selectable training models is generated by a premises device of a third party premises, and wherein the third party premises is associated with the premises;

providing a list of the plurality of selectable training models to a user interface; and

obtaining an indication of a selected training model from the list of the plurality of selectable training models via the user interface.

6. The device of claim 5, wherein the operations further comprise:

receiving update information for the plurality of selectable training models; and

providing the update information to the network, wherein the network modifies the plurality of selectable training models according to the update information.

7. The device of claim 4, wherein the operations further comprise analyzing the adjusted aggregated video content according to the adjusted training model to edit the adjusted aggregated video content to include a third subset of the images while excluding a fourth subset of the images.

8. The device of claim 1, wherein the analyzing the aggregated video content further comprises identifying a motion of an object in an images of the images of the plurality of events.

9. The device of claim 8, wherein the identifying the motion of the object further comprises identifying the object as a person and determining if the person is associated with the premises.

10. The device of claim 9, wherein the determining whether the person is associated with premises further comprises transmitting an alarm notification responsive to determining that the person is not associated with the premises.

11. A machine-readable storage medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, comprising:

receiving video content from a plurality of cameras associated with a premises;

generating aggregated video content for the premises from images of a plurality of events from the plurality of cameras;

analyzing the aggregated video content according to a training model to generate adjusted aggregated video content including a first subset of images while excluding a second subset of the images, wherein the first subset of images is determined by the training model based on a plurality of characteristics for the premises;

providing the adjusted aggregated video content including the first subset of images for presentation at a media processor associated with the premises;

receiving user-generated input for the adjusted aggregated video content, wherein the user-generated input provides identifications for the first subset of the images in the aggregated video content as the plurality of characteristics for the premises; and

adjusting the training model according to the user-generated input resulting in an adjusted training model.

12. The machine-readable storage medium of claim 11, wherein the analyzing the aggregated video content further comprises identifying a motion of an object in the first subset of images.

13. The machine-readable storage medium of claim 12, wherein the operations further comprise analyzing the object, wherein the object is determined to be a vehicle that has approached the premises, and wherein the vehicle is identified as being associated with the premises.

14. The machine-readable storage medium of claim 12, wherein the operations further comprise analyzing the object to identify the object as a person and determining whether the person is associated with the premises.

15. The machine-readable storage medium of claim 14, wherein the operations further comprise transmitting an alarm notification responsive to determining that the person is not associated with the premises.

16. A method, comprising:

aggregating, by a processing system comprising a processor, video content from a plurality of cameras to generate aggregated video content for the plurality of cameras;

analyzing, by the processing system, the aggregated video content according to a training model to generate adjusted aggregated video content to include first video content from the plurality of cameras while excluding second video content from the plurality of cameras;

sending, by the processing system, the adjusted aggregated video content to a display device associated with the processing system;

receiving user-generated input for the adjusted aggregated video content, wherein the user-generated input provides identifications for first video content in the aggregated video content; and

adjusting the training model according to the user-generated input resulting in an adjusted training model.

17. The method of claim 16, further

comprising providing the adjusted training model to a network,

wherein the analyzing the aggregated video content further comprises applying the adjusted training model to the aggregated video content.

18. The method of claim 17, further comprising:

receiving a plurality of selectable training models from a network, wherein one of the plurality of selectable training models is generated by a premises device of a third party premises, and wherein the third party premises is associated with the processing system;

providing a list of the plurality of selectable training models to a user interface; and

obtaining an indication of the training model from the list of the plurality of selectable training models via the user interface.

19. The method of claim 16, further comprising:

identifying a plurality of characteristics for a premises associated with the processing system; and

providing the plurality of characteristics to a network, wherein the training model is received from the network based on the plurality of characteristics.

20. The method of claim 19, wherein the plurality of characteristics for the premises includes neighborhood events, neighborhood information, neighbor information, visitor information, and delivery event information.