Method and system for aggregating video content
First Claim
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;
receiving video content from each of a plurality of cameras oriented toward a current premises resulting in a plurality of video content, wherein the plurality of video content comprises images of a plurality of events;
aggregating the plurality of video content to generate aggregate video content;
applying a selected training model to the aggregate video content resulting in adjusted aggregate video content, wherein the adjusted aggregate video content comprises a first subset of the images and does not comprise a second subset of the images, and wherein the first subset of the images is determined by the selected training model based on a plurality of categories corresponding to the plurality of events;
presenting the adjusted aggregate video content;
receiving user-generated input for the adjusted aggregate video content, wherein the user-generated input provides identifications for the first subset of the images in the aggregate video content;
adjusting the selected training model according to the user-generated input resulting in an adjusted training model; and
providing the adjusted training model to a network device.
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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.
44 Citations
20 Claims
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1. A device, comprising:
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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; receiving video content from each of a plurality of cameras oriented toward a current premises resulting in a plurality of video content, wherein the plurality of video content comprises images of a plurality of events; aggregating the plurality of video content to generate aggregate video content; applying a selected training model to the aggregate video content resulting in adjusted aggregate video content, wherein the adjusted aggregate video content comprises a first subset of the images and does not comprise a second subset of the images, and wherein the first subset of the images is determined by the selected training model based on a plurality of categories corresponding to the plurality of events; presenting the adjusted aggregate video content; receiving user-generated input for the adjusted aggregate video content, wherein the user-generated input provides identifications for the first subset of the images in the aggregate video content; adjusting the selected training model according to the user-generated input resulting in an adjusted training model; and providing the adjusted training model to a network device. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A machine-readable storage medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, comprising:
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receiving a plurality of video content associated with a current premises wherein the plurality of video content comprises images of a plurality of events; aggregating the plurality of video content to generate aggregate video content; applying a selected training model to the aggregate video content resulting in adjusted aggregate video content, wherein the adjusted aggregate video content comprises a first subset of the images and does not comprise a second subset of the images, and wherein the first subset of the images is determined by the selected training model based on a plurality of categories corresponding to the plurality of events, and wherein the selected training model is selected according to a plurality of characteristics of the current premises; presenting the adjusted aggregate video content; receiving user-generated input for the adjusted aggregate video content, wherein the user-generated input provides identifications for the first subset of the images in the aggregate video content; adjusting the selected training model according to the user-generated input resulting in an adjusted training model; and providing the adjusted training model to a network device. - View Dependent Claims (11, 12, 13)
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14. A method, comprising:
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receiving, by a processing system including a processor, video content from each of a plurality of cameras oriented toward a current premises resulting in a plurality of video content, wherein the plurality of video content comprises images of a plurality of events; aggregating, by the processing system, the plurality of video content to generate aggregate video content; adjusting, by the processing system, the aggregate video content resulting in adjusted aggregate video content according to a training model, wherein the adjusted aggregate video content comprises a first subset of the images and does not comprise a second subset of the images, and wherein the first subset of the images is determined by the training model based on a plurality of categories corresponding to the plurality of events; presenting, by the processing system, the adjusted aggregate video content; receiving, by the processing system, identifications for the first subset of the images in the aggregate video content; adjusting, by the processing system, the training model according to the identifications resulting in an adjusted training model; and providing, by the processing system, the adjusted training model to a network device. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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Specification