Scene preset identification using quadtree decomposition analysis
First Claim
1. A computer-implemented method for identifying a scene preset for a background scene depicted in a stream of video images captured via a video camera, comprising:
- receiving the background scene;
generating a quadtree decomposition of the background scene, the quadtree decomposition including a plurality of window portions of the background scene;
determining if the background scene matches one of a plurality of stored scene presets, each representing a previously captured background scene determined for a distinct field-of-view of the camera, based on the plurality of window portions of the background scene;
upon determining the background scene matches the stored scene preset that represents the previously captured background scene;
updating the stored scene preset, andrestoring a learning state associated with the stored scene preset used by a machine-learning engine;
upon determining the background scene does not match the stored scene preset that represents the previously captured background scene, creating a new scene preset;
computing a phase spectrum for each window portion of the plurality of window portions of the background scene;
projecting the phase spectra onto corresponding preset image matrices of a quadtree decomposition of the stored scene preset; and
computing a reconstruction score for the background scene that indicates how closely the background scene matches the previously captured background scene.
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Abstract
Techniques are disclosed for matching a current background scene of an image received by a surveillance system with a gallery of scene presets that each represent a previously captured background scene. A quadtree decomposition analysis is used to improve the robustness of the matching operation when the scene lighting changes (including portions containing over-saturation/under-saturation) or a portion of the content changes. The current background scene is processed to generate a quadtree decomposition including a plurality of window portions. Each of the window portions is processed to generate a plurality of phase spectra. The phase spectra are then projected onto a corresponding plurality of scene preset image matrices of one or more scene preset. When a match between the current background scene and one of the scene presets is identified, the matched scene preset is updated. Otherwise a new scene preset is created based on the current background scene.
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Citations
19 Claims
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1. A computer-implemented method for identifying a scene preset for a background scene depicted in a stream of video images captured via a video camera, comprising:
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receiving the background scene; generating a quadtree decomposition of the background scene, the quadtree decomposition including a plurality of window portions of the background scene; determining if the background scene matches one of a plurality of stored scene presets, each representing a previously captured background scene determined for a distinct field-of-view of the camera, based on the plurality of window portions of the background scene; upon determining the background scene matches the stored scene preset that represents the previously captured background scene; updating the stored scene preset, and restoring a learning state associated with the stored scene preset used by a machine-learning engine; upon determining the background scene does not match the stored scene preset that represents the previously captured background scene, creating a new scene preset; computing a phase spectrum for each window portion of the plurality of window portions of the background scene; projecting the phase spectra onto corresponding preset image matrices of a quadtree decomposition of the stored scene preset; and computing a reconstruction score for the background scene that indicates how closely the background scene matches the previously captured background scene. - View Dependent Claims (2, 3, 4, 7, 8)
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5. A computer-implemented method for identifying a scene preset for a background scene depicted in a stream of video images captured via a video camera, comprising:
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receiving the background scene; generating a quadtree decomposition of the background scene, the quadtree decomposition including a plurality of window portions of the background scene; determining that a first window portion of the quadtree decomposition of the background scene is over-saturated; discarding the first window portion of the quadtree decomposition of the background scene; determining if the background scene matches one of a plurality of stored scene presets, each representing a previously captured background scene determined for a distinct field-of-view of the camera, based on the plurality of window portions of the background scene without the first window portion; upon determining the background scene matches the stored scene preset that represents the previously captured background scene; updating the stored scene preset, and restoring a learning state associated with the stored scene preset used by a machine-learning engine; and upon determining the background scene does not match the stored scene preset that represents the previously captured background scene, creating a new scene preset.
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6. A computer-implemented method for identifying a scene preset for a background scene depicted in a stream of video images captured via a video camera, comprising:
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receiving the background scene; generating a quadtree decomposition of the background scene, the quadtree decomposition including a plurality of window portions of the background scene; determining that a first window portion of the quadtree decomposition of the background scene is under-saturated; discarding the first window portion of the quadtree decomposition of the background scene; determining if the background scene matches one of a plurality of stored scene presets, each representing a previously captured background scene determined for a distinct field-of-view of the camera, based on the plurality of window portions of the background scene without the first window portion; upon determining the background scene matches the stored scene preset that represents the previously captured background scene; updating the stored scene preset, and restoring a learning state associated with the stored scene preset used by a machine-learning engine; and upon determining the background scene does not match the stored scene preset that represents the previously captured background scene, creating a new scene preset.
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9. A non-transitory computer-readable storage medium containing a program which, when executed by a processor, performs an operation for identifying a scene preset for a background scene of in a stream of video images captured via a video camera, the operation comprising:
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receiving the background scene; generating a quadtree decomposition of the background scene, the quadtree decomposition including a plurality of window portions of the background scene; and determining if the background scene matches one of a plurality of stored scene presets, each representing a previously captured background scene determined for a distinct field-of-view of the camera, based on the plurality of window portions of the background scene; upon determining the background scene matches the stored scene preset that represents the previously captured background scene; updating the stored scene preset; restoring a learning state associated with the stored scene preset used by a machine-learning engine; upon determining the background scene does not match the stored scene preset that represents the previously captured background scene, creating a new scene preset; computing a phase spectrum for each window portion of the plurality of window portions of the background scene; projecting the phase spectra onto corresponding preset image matrices of a quadtree decomposition of the stored scene preset; and computing a reconstruction score for the background scene that indicates how closely the background scene matches the stored scene preset that represents the previously captured background scene. - View Dependent Claims (10, 12)
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11. A non-transitory computer-readable storage medium containing a program which, when executed by a processor, performs an operation for identifying a scene preset for a background scene of a stream of video images captured via a video camera, the operation comprising:
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receiving the background scene; generating a quadtree decomposition of the background scene, the quadtree decomposition including a plurality of window portions of the background scene; determining that a first window portion of the quadtree decomposition of the background scene is over-saturated or under-saturated; discarding the first window portion of the quadtree decomposition of the background scene; determining if the background scene matches one of a plurality of stored scene presets, each representing a previously captured background scene determined for a distinct field-of-view of the camera, based on the plurality of window portions of the background scene without the first window portion; upon determining the background scene matches the stored scene preset that represents the previously captured background scene; updating the stored scene preset, and restoring a learning state associated with the stored scene preset used by a machine-learning engine; upon determining the background scene does not match the stored scene preset that represents the previously captured background scene, creating a new scene preset.
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13. A system, comprising:
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a video input source configured to capture images; a processor; and a memory containing a program, which, when executed on the processor is configured to perform an operation for identifying a scene preset for a background scene of a stream of video images captured by the video input source, the operation comprising; receiving the background scene, generating a quadtree decomposition of the background scene, the quadtree decomposition including a plurality of window portions of the background scene, determining if the background scene matches one of a plurality of stored scene presets, each representing a previously captured background scene determined for a distinct field-of-view of the video input source, based on the plurality of window portions of the background scene, upon determining the background scene matches the stored scene preset that represents the previously captured background scene; updating the scene preset; and restoring a learning state associated with the stored scene preset used by a machine-learning engine; upon determining the background scene does not match the stored scene preset that represents the previously captured background scene, creating a new scene preset, computing a phase spectrum for each window portion of the plurality of window portions of the background scene, projecting the phase spectra onto corresponding preset image matrices of a quadtree decomposition of the stored scene preset, and computing a reconstruction score for the background scene that indicates how closely the background scene matches the previously captured background scene. - View Dependent Claims (14, 15, 16, 17)
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18. A system, comprising:
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a video input source configured to capture images; a processor; and a memory containing a program, which, when executed on the processor is configured to perform an operation for identifying a scene preset for a background scene of a stream of video images captured by the video input source, the operation comprising; receiving the background scene; generating a quadtree decomposition of the background scene, the quadtree decomposition including a plurality of window portions of the background scene; determining that a first window portion of the quadtree decomposition of the background scene is over-saturated; discarding the first window portion of the quadtree decomposition of the background scene; determining if the background scene matches one of a plurality of stored scene presets, each representing a previously captured background scene determined for a distinct field-of-view of the camera, based on the plurality of window portions of the background scene without the first window portion; upon determining the background scene matches the stored scene preset that represents the previously captured background scene; updating the scene preset, and restoring a learning state associated with the stored scene preset used by a machine-learning engine; and upon determining the background scene does not match the stored scene preset that represents the previously captured background scene, creating a new scene preset.
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19. A system, comprising:
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a video input source configured to capture images; a processor; and a memory containing a program, which, when executed on the processor is configured to perform an operation for identifying a scene preset for a background scene of a stream of video images captured by the video input source, the operation comprising; receiving the background scene; generating a quadtree decomposition of the background scene, the quadtree decomposition including a plurality of window portions of the background scene; determining that a first window portion of the quadtree decomposition of the background scene is under-saturated; discarding the first window portion of the quadtree decomposition of the background scene; determining if the background scene matches one of a plurality of stored scene presets, each representing a previously captured background scene determined for a distinct field-of-view of the camera, based on the plurality of window portions of the background scene without the first window portion; upon determining the background scene matches the stored scene preset that represents the previously captured background scene; updating the scene preset, and restoring a learning state associated with the stored scene preset used by a machine-learning engine; and upon determining the background scene does not match the stored scene preset that represents the previously captured background scene, creating a new scene preset.
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Specification