Robust and efficient foreground analysis for real-time video surveillance
First Claim
1. A method for foreground analysis in real-time video, comprising the steps of:
- determining mixtures of Gaussians for different aspects of an image;
detecting a static foreground region by using the mixtures of Gaussians to identify whether a pixel belongs to the static region or a background region; and
processing the image in accordance with two or more of;
detecting a static region to determine objects in a scene using the mixtures of Gaussians of the background region;
integrating texture information of the background image to a foreground mask to remove false positive foreground areas resulting from lighting changes; and
integrating pixel intensity information by determining a cross-correlation of intensities between a current frame and the background image for each pixel in a foreground mask to remove image shadows.
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Abstract
Systems and methods for foreground analysis in real-time video include background subtraction and foreground detection, shadow removal, quick lighting change adaptation, static foreground region detection, foreground fragment reduction, and frame level change detection. Processes include background image extraction and foreground detection, integrating texture information of the background image and a current frame to remove false positive foreground areas resulting from lighting changes, integrating pixel intensity information by determining a cross-correlation of intensities between a current frame and the background image for each pixel in a foreground mask to remove image shadows. Static foreground region detection and fragment reduction are also included.
39 Citations
24 Claims
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1. A method for foreground analysis in real-time video, comprising the steps of:
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determining mixtures of Gaussians for different aspects of an image; detecting a static foreground region by using the mixtures of Gaussians to identify whether a pixel belongs to the static region or a background region; and processing the image in accordance with two or more of; detecting a static region to determine objects in a scene using the mixtures of Gaussians of the background region; integrating texture information of the background image to a foreground mask to remove false positive foreground areas resulting from lighting changes; and integrating pixel intensity information by determining a cross-correlation of intensities between a current frame and the background image for each pixel in a foreground mask to remove image shadows. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method for foreground analysis in real-time video, comprising the steps of:
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determining mixtures of Gaussians for different aspects of an image; detecting a static region by using the mixtures of Gaussians to identify whether a pixel belongs to the static region or a background region; and reducing foreground fragments by pushing back the entire static region back to the background region at a point when the static region is largest. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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17. A system for foreground analysis in real-time video, comprising:
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a background subtraction module which determines a mixture of Gaussians for a background region of an image and subtracts out portions of the image in accordance with an integration module; and the integration module detects at least static regions by using the mixtures of Gaussians to identity whether a pixel belongs to the static region or the background region and reduces foreground fragments of the static regions by pushing back each entire static region to the background region at a point when the static region is largest. - View Dependent Claims (18, 19, 20, 21, 22, 23, 24)
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Specification