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Video segmentation using statistical pixel modeling
| Details |
Inventors: Lipton, Alan J.; Allmen, Mark; Haering, Niels; Severson, William; Strat, Thomas M.;
Assignee: DiamondBack Vision, Inc. (Reston, VA)
Primary Examiner: Johns; Andrew W.
Assistant Examiner: Alavi; Amir
Attorney, Agent or Firm: Venable LLP, Gluck; Jeffrey W.
A method for segmenting video data into foreground and background portions utilizes statistical modeling of the pixels. A statistical model of the background is built for each pixel, and each pixel in an incoming video frame is compared with the background statistical model for that pixel. Pixels are determined to be foreground or background based on the comparisons. |
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DETAILED DESCRIPTION The present invention is directed to a method for segmentation of video into foreground information and background information, based on statistical properties of the source video.
More particularly, the method is based on creating and updating statistical information pertaining to a characteristic of regions of the video and the labeling of those regions (i.
e.
, as foreground or background) based on the statistical information.
For example, in one embodiment, the regions are pixels, and the characteristic is chromatic intensity.
Many other possibilities exist, as will become apparent.
In embodiments of the invention, a background model is developed containing at least two components.
A first component is the scene model, which may be built and updated, for example, as discussed in the aforementioned U.
S.
patent applications.
A second component is a background statistical model.
In a first embodiment, the inventive method comprises a two-pass process of video segmentation.
The two passes of the embodiment comprise a first pass in which a background statistical model is built and updated and a second pass in which regions in the frames are segmented.
An embodiment of the first pass comprises steps of aligning each video frame with a scene model and updating the background statistical model based on the aligned frame data.
An embodiment of the second pass comprises, for each frame, steps of labeling regions of the frame and performing spatial filtering.
In a second embodiment, the inventive method comprises a one-pass process of video segmentation.
The single pass comprises, for each frame in a frame sequence of a video stream, steps of aligning the frame with a scene model; building a background statistical model; labeling the regions of the frame, and performing spatial/temporal filtering.
In yet another embodiment, the inventive method comprises a modified version of the aforementioned one-pass process of video segmentation.
This embodiment is similar to the previous embodiment, except that the step of building a background statistical model is replaced with a step of building a background statistical model and a secondary statistical model
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Image Analysis 
