Progressive shape based encoding of video content within a swarm environment
Embodiments are directed towards employing distributed computing concepts such as peer-to-peer processing to distribute across a plurality of peer client devices, or swarm, the computations of Shape Encoding Schemes (SES) for encoding digital video content. As more peer client devices receive the content, progressively more iterations of a SES encoding is performed on various frames within the video content, thereby improving the encoding of the overall video content. Optionally, such distributed progressive processing or swarming approach may include other encoding, such as scaling corrections, scene transitions corrections, and the like.
1. a network device, comprising:
a transceiver to send and receive data over a network; and
a processor that is operative on the received data to perform actions, including:
distributing a plurality of frames within a video content to a plurality of different peer-to-peer configured client devices, wherein each client device within the plurality is configured to select or be instructed to select at least one frame from the plurality of frames, and to perform at least one iteration of a progressive Shape Encoding Scheme (SES) encoding upon the selected at least one frame;
receiving at least one resulting output frame from a client device within the plurality of client devices, the at least one resulting output frame generated by the client device performing at least one iteration of the progressive SES encoding on the at least one selected frame;
if the received at least one resulting output frame indicates that a global convergence threshold is unsatisfied for a resulting output frame of the progressive SES encoding of the selected frame, then sending the resulting output frame to another one of the peer-to-peer configured client devices to perform at least one iteration of the progressive SES encoding upon the resulting output frame; and
if the received at least one resulting output frame indicates that the global convergence threshold is satisfied for the resulting output frame, sending the resulting output frame to each of the other peer-to-peer configured client devices to replace the corresponding selected frame in at least a partially encoded form of the video content;
wherein the set of iteration parameters at each of the plurality of peer-to-peer configured client computing devices is based at least in part on bad path information;
wherein analyzing the received block includes determining whether a resulting output frame of the iterative fractal compression process on the block satisfies a global convergence threshold; and
wherein the iterative fractal compression process is performed between one and five times by each of the plurality of peer-to-peer configured client computing devices.
2. a method of performing fractal compression of video content in a distributed computing environment, the method comprising:
transmitting, to each of a plurality of peer-to-peer configured client computing devices, a block including a plurality of frames within a video content;
receiving, at a network device, a block including frames generated by performing at least one iteration of an iterative fractal compression process upon the plurality of frames at one of the plurality of peer-to-peer configured client computing devices applying a set of iteration parameters including a fractal scaling parameter defining a scaling factor to be applied to the video content; and
analyzing, at the network device, the received block to determine whether the received block is to be selected for use as a resulting output frame in at least a partially encoded form of the video content.
3. The method of claim 2 , wherein the set of iteration parameters at each of the plurality of peer-to-peer configured client computing devices includes a number of color bits used to describe an image.
4. The method of claim 2 , wherein each of the peer-to-peer configured client computing devices applies a different set of iteration parameters from the other of the plurality of peer-to-peer configured client computing devices.
5. The method of claim 2 , wherein the scaling factor is in the range of about ¼ to about 1.
6. The method of claim 2 , wherein the iterative fractal compression process is performed between one and five times by each of the plurality of peer-to-peer configured client computing devices.
7. The method of claim 2 , wherein the interactive fractal compression process performs a shape-based encoding scheme.
8. The method of claim 7 , wherein the shape-based encoding scheme comprises a progressive Shape Encoding Scheme (SES) encoding on at least one frame of the plurality of frames.
9. a system, comprising:
a network device, comprising:
a transceiver to send and receive data over a network; and
a processor that is operative on the received data to perform actions, including:
distributing a plurality of frames within a video content to a plurality of different peer-to-peer configured client devices, wherein each client device within the plurality is configured to select or be instructed to select at least one frame from the plurality of frames, and to perform at least one iteration of an iterative fractal encoding process upon the selected frame, the iterative fractal encoding process performed using a plurality of encoding parameters, the plurality of encoding parameters including a fractal scaling parameter defining a scaling factor to be applied to the video content;
receiving a block including at least one frame generated by performing at least one iteration of the iterative fractal encoding process on the at least one selected frame from one or more client devices within the plurality of client devices; and
analyzing the received block to determine whether the received block is to be selected for use as a resulting output frame in at least a partially encoded form of the video content;
wherein each of the plurality of peer-to-peer configured client computing devices applies a set of iteration parameters based at least in part on bad path information;
wherein each of the peer-to-peer configured client computing devices applies a different set of iteration parameters from the other of the plurality of peer-to-peer configured client computing devices; and
wherein analyzing the received block includes determining whether a resulting output frame of the iterative fractal compression process on the block satisfies a global convergence threshold.
10. The system of claim 9 , wherein each of the plurality of peer-to-peer configured client computing devices applies a set of iteration parameters, including includes a number of color bits used to describe an image.
11. The system of claim 9 , wherein the iterative fractal encoding process performs a shape-based encoding scheme.
12. The system of claim 11 , wherein the shape-based encoding scheme comprises a progressive Shape Encoding Scheme (SES) encoding on at least one frame of the plurality of frames.
13. The system of claim 9 , further comprising a plurality of different peer-to-peer configured client devices configured to perform at least one iteration of an iterative fractal encoding process upon the selected frame as received from the network device.
14. The system of claim 9 , wherein the scaling factor is in the range of about ¼ to about 1.