Systems and methods for generating composite media using distributed networks
A distributed systems and methods for generating composite media including receiving a media context that defines media that is to be generated, the media context including: a definition of a sequence of media segment specifications and, an identification of a set of remote devices. For each media segment specification, a reference segment may be generated and transmitted to at least one remote device. A media segment may be received from each of the remote device, the media segment having been recorded by a camera. Verified media sequences may replace the corresponding reference segment. The media segments may be aggregated and an updated sequence of media segments may be defined. An instance of the media context that includes a subset of the updated sequence of media segments may then be generated.
1 . A computer-implemented method comprising:
accessing a media context that defines media, the media context including an identification of a specification of a first media segment and one or more quality metrics;
accessing one or more first media segments;
receiving an input that includes information indicative of a target second media segment, wherein the information includes at least part of a storyboard specifying one or more tasks for completion by one or more artificial-intelligence agents;
identifying, using an artificial-intelligence agent technique, a reference segment to supplement the first media segment based on: the one or more first media segments, the media context, and the input;
transmitting the reference segment to at least one remote device;
receiving, from the at least one remote device, the target second media segment based on the reference segment, wherein the target second media segment is recorded using a camera of the at least one remote device;
verifying the target second media segment based on the one or more quality metrics or the storyboard; and
outputting a sequence of media segments from the one or more first media segments and the target second media segment based on the one or more tasks.
2 . The computer-implemented method of claim 1 , wherein the artificial-intelligence agent technique is configured to convolve one or more space-time kernels.
3 . The computer-implemented method of claim 1 , further comprising:
generating the sequence of media segments including the media segment and one or more other media segments corresponding to the reference segment.
4 . The computer-implemented method of claim 1 , wherein the reference segment corresponds to virtual time points that follow time points of the one or more first media segments.
5 . The computer-implemented method of claim 1 , wherein the one or more first media segments include multiple frames of video data.
6 . The computer-implemented method of claim 1 , wherein the input that includes the information indicative the target second media segment includes a textual or verbal description of a visual context of the target second media.
7 . The computer-implemented method of claim 1 , further comprising:
identifying an object or action that is to be included in the one or more first media segments, wherein new content is identified using the identified object or action.
8 . A system comprising:
one or more processors; and
a computer-readable medium storing instructions that when executed by one or more processors, cause the one or more processors to perform operations including:
accessing a media context that defines media, the media context including an identification of a specification of a first media segment and one or more quality metrics;
accessing one or more first media segments;
receiving an input that includes information indicative of a target second media segment, wherein the information includes at least part of a storyboard specifying one or more tasks for completion by one or more artificial-intelligence agents;
identifying, using an artificial-intelligence agent technique, a reference segment to supplement the first media segment based on: the one or more first media segments, the media context, and the input;
transmitting the reference segment to at least one remote device;
receiving, from the at least one remote device, the target second media segment based on the reference segment, wherein the target second media segment is recorded using a camera of the at least one remote device;
verifying the target second media segment based on the one or more quality metrics or the storyboard; and
outputting a sequence of media segments from the one or more first media segments and the target second media segment based on the one or more tasks.
9 . The system of claim 8 , wherein the artificial-intelligence agent technique is configured to convolve one or more space-time kernels.
10 . The system of claim 8 , wherein the operations further include:
generating the sequence of media segments including the media segment and one or more other media segments corresponding to the reference segment.
11 . The system of claim 8 , wherein the reference segment corresponds to virtual time points that follow time points of the one or more first media segments.
12 . The system of claim 8 , wherein the one or more first media segments include multiple frames of video data.
13 . The system of claim 8 , wherein the input that includes the information indicative the target second media segment includes a textual or verbal description of a visual context of the target second media.
14 . A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause one or more data processors to perform operations including:
accessing a media context that defines media, the media context including an identification of a specification of a first media segment and one or more quality metrics;
accessing one or more first media segments;
receiving an input that includes information indicative of a target second media segment, wherein the information includes at least part of a storyboard specifying one or more tasks for completion by one or more artificial-intelligence agents;
identifying, using an artificial-intelligence agent technique, a reference segment to supplement the first media segment based on: the one or more first media segments, the media context, and the input;
transmitting the reference segment to at least one remote device;
receiving, from the at least one remote device, the target second media segment based on the reference segment, wherein the target second media segment is recorded using a camera of the at least one remote device;
verifying the target second media segment based on the one or more quality metrics or the storyboard; and
outputting a sequence of media segments from the one or more first media segments and the target second media segment based on the one or more tasks.
15 . The computer-program product of claim 14 , wherein the artificial-intelligence agent technique is configured to convolve one or more space-time kernels.
16 . The computer-program product of claim 14 , wherein the operations further include:
generating the sequence of media segments including the media segment and one or more other media segments corresponding to the reference segment.
17 . The computer-program product of claim 14 , wherein the reference segment corresponds to virtual time points that follow time points of the one or more first media segments.
18 . The computer-program product of claim 14 , wherein the one or more first media segments include multiple frames of video data.
19 . The computer-program product of claim 14 , wherein the input that includes the information indicative the target second media segment includes a textual or verbal description of a visual context of the target second media.
20 . The computer-program product of claim 14 , wherein the operations further include:
identifying an object or action that is to be included in the one or more first media segments, wherein new content is identified using the identified object or action.