1. A computer-implemented image processing method, comprising:
receiving, using at least one processing circuit, a plurality of image frames of a video;
constructing, using at least one processing circuit, a plurality of statistical models of the plurality of image frames at a plurality of pixel granularity levels;
constructing, using at least one processing circuit, a plurality of probabilistic models of an input image frame at a plurality of channel granularity levels based on the plurality of statistical models;
merging at least some of the plurality of probabilistic models based on a weighted average to form a single probability image; and
determining background pixels, based on a probability threshold value, from the single probability image, wherein the plurality of statistical models comprise spatio-temporal (S-T) histogram for each of the pixels from the plurality of image frames, wherein a horizontal axis of the S-T histogram represents channel value bins, and wherein a vertical axis of the S-T histogram represents counts of image frames per bin.
2. The method of claim 1, wherein the plurality of probabilistic models comprise:
a probability image from each of the S-T histogram, wherein each of the probability images comprises a plurality of pixels each indicating a probability of a corresponding pixel in the input image being a background pixel; and
compact probability images from the probability images.
3. The method of claim 2, wherein the compact probability images are obtained from one of a mean, a median, or a minimum operation over the probability images.
4. The method of claim 2, wherein the compact probability images include:
a compact S-T probability image;
a compact aggregate background probability image across a first-order approximation of a background region; and
a compact aggregate foreground probability image across a first-order approximation of a foreground region,
wherein the compact S-T probability image is given a higher weight in the weighted average.
5. The method of claim 1, wherein the weighted average gives a higher weight to the probabilistic models at a lower pixel granularity level.
6. The method of claim 1, further comprising:
subsampling pixels in the single probability image,
wherein the background pixels are determined from the subsampled single probability image.
7. The method of claim 1, further comprising automatically replacing the determined background pixels with desired pixel values.
8. The method of claim 1, further comprising alpha-blending the determined background pixels with foreground pixels.
9. The method of claim 1, wherein each pixel of each of the plurality of image frames has a blue channel, a green channel, a red channel, and an alpha channel.
10. The method of claim 1, wherein each pixel of each of the plurality of image frames has a blue channel, a green channel, and a red channel.
11. The method of claim 1, further comprising:
adding and subtracting image frames to the plurality of image frames; and
updating the plurality of statistical models and the plurality of probabilistic models based on the plurality of image frames with the added and subtracted image frames.
12. The method of claim 1, further comprising:
sampling one of the plurality of image frames at a probability equal to a desired statistics update frequency.
13. An image processing system comprising at least one processing circuit configured to:
receive a plurality of image frames of a video;
construct a plurality of statistical models of the plurality of image frames at a plurality of pixel granularity levels;
construct a plurality of probabilistic models of an input image frame at a plurality of channel granularity levels based on the plurality of statistical models;
merge at least some of the plurality of probabilistic models based on a weighted average to form a single probability image; and
determine background pixels, based on a probability threshold value, from the single probability image wherein the plurality of statistical models comprise spatio-temporal (S-T) histogram for each of the pixels from the plurality of image frames, wherein a horizontal axis of the S-T histogram represents channel value bins, and wherein a vertical axis of the S-T histogram represents counts of image frames per bin.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method of providing communication circuit status information via a network interface session, wherein the method comprises:
receiving a status report request from a network service provider technician;
determining a network service provider for whom the technician requesting the status report works;
the status report request identifying at least one communication circuit identifier for which the network service provider technician request status;
determining an entity operating the at least one communication circuit;
comparing the entity to the network service provider;
terminating access to the communications circuit status information if the entity is not the network service provider;
communicating the at least one communication circuit identifier to a circuit database server;
receiving a circuit verification for each at least one communication circuit identifier;
communicating the status report to the circuit database server;
receiving circuit status information from the circuit database server;
creating a status report comprising the circuit status information; and
transmitting the status report to a follow-on system.
2. The method of claim 1, further comprising receiving technician identification parameters.
3. The method of claim 2, further comprising communicating the technician identification parameters to a technician authorization database.
4. The method of claim 3, further comprising receiving a technician access authorization from the technician authorization database.
5. The method of claim 1, wherein the status report comprises an installation date for the at least one communication circuit identifier.
6. The method of claim 1, wherein the follow-on system comprises a remotely located computer for display of said status report.
7. The method of claim 1, wherein the follow-on system comprises a storage system.
8. The method of claim 1 wherein the follow-on system comprises an email system.
9. The method of claim 1, wherein the circuit verification comprises a circuit existence identifier and circuit ownership identifier value pair.