Video segmentation using statistical pixel modeling
First Claim
Patent Images
1. A method of one-pass video segmentation for differentiating between portions of video, the method comprising:
- obtaining, by a processor, two or more frames from a real-time video stream;
building, by the processor, a background model using the two or more frames;
labeling, by the processor, at least a portion of pixels in the two or more frames; and
performing spatial or temporal filtering on the two or more frames by the processor.
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Abstract
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. The method for segmenting video data may be further incorporated into a method for implementing an intelligent video surveillance system. The method for segmenting video data may be implemented in hardware.
234 Citations
25 Claims
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1. A method of one-pass video segmentation for differentiating between portions of video, the method comprising:
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obtaining, by a processor, two or more frames from a real-time video stream; building, by the processor, a background model using the two or more frames; labeling, by the processor, at least a portion of pixels in the two or more frames; and performing spatial or temporal filtering on the two or more frames by the processor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method of one-pass video segmentation for differentiating between portions of video, the method comprising:
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obtaining, by a processor, two or more frames from a real-time video stream; labeling, by the processor, at least a portion of pixels in the two or more frames; performing spatial or temporal filtering on the two or more frames by the processor; and updating, by the processor, a statistical model of the two or more frames. - View Dependent Claims (11, 12)
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13. A method of one-pass video segmentation, comprising:
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receiving, by a processor, two or more frames from a real-time video stream; comparing, by the processor, the received frames to a background model; labeling, by the processor, at least a portion of pixels in the received frames; performing spatial or temporal filtering on the two or more frames by the processor; and building or updating, by the processor, the background model of the received frames. - View Dependent Claims (14, 15, 16, 17, 18, 19)
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20. A non-transitory computer-readable medium comprising instructions executable by one or more processors to perform a one-pass video segmentation for differentiating between portions of video, the computer-readable medium comprising one or more instructions for:
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obtaining, by the one or more processors, two or more frames from a real-time video stream; building, by the one or more processors, a background model using the two or more frames; labeling, by the one or more processors, at least a portion of pixels in the two or more frames; and performing, by the one or more processors, spatial or temporal filtering on the two or more frames.
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21. A non-transitory computer-readable medium comprising instructions executable by one or more processors to perform a one-pass video segmentation for differentiating between portions of video, the computer-readable medium comprising one or more instructions for:
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obtaining, by the one or more processors, two or more frames from a real-time video stream; labeling, by the one or more processors, at least a portion of pixels in the two or more frames; performing, by the one or more processors, spatial or temporal filtering on the two or more frames; and updating, by the one or more processors, a statistical model of the two or more frames.
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22. A non-transitory computer-readable medium comprising instructions executable by one or more processors for one-pass video segmentation, the computer-readable medium comprising one or more instructions for:
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receiving, by the one or more processors, two or more frames from a real-time video stream; comparing, by the one or more processors, the received frames to a background model; labeling, by the one or more processors, at least a portion of pixels in the received frames; performing, by the one or more processors, spatial or temporal filtering on the two or more frames; and building or updating, by the one or more processors, the background model of the received frames.
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23. An apparatus for one-pass video segmentation for differentiating between portions of video, the apparatus comprising:
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at least one processor; a memory coupled to the at least one processor; and a computer program residing in memory and being executed by the at least one processor, wherein the computer program obtains two or more frames from a real-time video stream, builds a background model using the two or more frames, labels at least a portion of pixels in the two or more frames, and performs spatial or temporal filtering on the two or more frames.
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24. An apparatus for one-pass video segmentation for differentiating between portions of video, the apparatus comprising:
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at least one processor; a memory coupled to the at least one processor; and a computer program residing in memory and being executed by the at least one processor, wherein the computer program obtains two or more frames from a real-time video stream, labels at least a portion of pixels in the two or more frames, performs spatial or temporal filtering on the two or more frames, and updates a statistical model of the two or more frames.
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25. An apparatus for one-pass video segmentation, the apparatus comprising:
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at least one processor; a memory coupled to the at least one processor; and a computer program residing in memory and being executed by the at least one processor, wherein the computer program receives two or more frames from a real-time video stream, compares the received frames to a background model, labels at least a portion of pixels in the received frames, performs spatial or temporal filtering on the two or more frames, and builds or updates the background model of the received frames.
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Specification