Video/vision based access control method and system for parking occupancy determination, which is robust against abrupt camera field of view changes
First Claim
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1. A method for parking occupancy determination, said method comprising:
- measuring changes in a field of view using template matching between templates learned from at least one original scene and templates learned from at least one current scene with motion removed, wherein said at least current scene with motion removed comprises a motion-removed current scene;
employing said changes measured in said field of view to adjust data indicative of at least one region of interest for vision-based processing thereof if said changes measured are above a pre-determined threshold so that an impact of said changes with respect to said field of view to performance is minimized; and
applying diagnostics with respect to said field of view without compensation to assist in remotely repositioning a camera associated with said field of view back to said at least one original scene,wherein said templates comprise at least one M×
N sub-image derived from said at least one original scene and said at least one current scene with said motion removed; and
said template matching is based on a normalized cross-correlation value as a similarity metric, wherein at run-time each image template among said templates slides against said motion-removed current scene and a location is determined, which yields a highest normalized cross-correlation value, said normalized cross-correlation value comprising said highest normalized cross correlation value.
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Abstract
Methods, systems and processor-readable media for parking occupancy determination. Changes in the field of view can be measured using template matching between templates derived from an original scene and a current scene with motion removed. The changes measured in the field of view can be employed to adjust data indicative of a region of interest for vision-based processing thereof if the changes measured are above a pre-determined threshold so that the impact of the changes with respect to the field of view to performance is minimized.
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Citations
16 Claims
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1. A method for parking occupancy determination, said method comprising:
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measuring changes in a field of view using template matching between templates learned from at least one original scene and templates learned from at least one current scene with motion removed, wherein said at least current scene with motion removed comprises a motion-removed current scene; employing said changes measured in said field of view to adjust data indicative of at least one region of interest for vision-based processing thereof if said changes measured are above a pre-determined threshold so that an impact of said changes with respect to said field of view to performance is minimized; and applying diagnostics with respect to said field of view without compensation to assist in remotely repositioning a camera associated with said field of view back to said at least one original scene, wherein said templates comprise at least one M×
N sub-image derived from said at least one original scene and said at least one current scene with said motion removed; andsaid template matching is based on a normalized cross-correlation value as a similarity metric, wherein at run-time each image template among said templates slides against said motion-removed current scene and a location is determined, which yields a highest normalized cross-correlation value, said normalized cross-correlation value comprising said highest normalized cross correlation value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A system for parking occupancy determination, said system comprising:
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a processor; and a non-transitory computer-usable medium embodying computer program code, said computer-usable medium capable of communicating with the processor, said computer program code comprising instructions executable by said processor and configured for; measuring changes in a field of view using template matching between templates learned from at least one original scene and templates learned from at least one current scene with motion removed, wherein said at least current scene with motion removed comprises a motion-removed current scene; employing said changes measured in said field of view to adjust data indicative of at least one region of interest for vision-based processing thereof if said changes measured are above a predetermined threshold so that an impact of said changes with respect to said field of view to performance is minimized; and applying diagnostics with respect to said field of view without compensation to assist in remotely repositioning a camera associated with said field of view back to said at least one original scene, wherein said templates comprise at least one M×
N sub-image derived from said at least one original scene and said at least one current scene with said motion removed; andsaid template matching is based on a normalized cross-correlation value as a similarity metric, wherein at run-time each image template among said templates slides against said motion-removed current scene and a location is determined, which yields a highest normalized cross-correlation value, said normalized cross-correlation value comprising said highest normalized cross correlation value. - View Dependent Claims (10, 11, 12, 13, 14, 15)
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16. A non-transitory processor-readable medium storing code representing instructions to cause a process for parking occupancy determination, said code comprising code to:
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measure changes in a field of view using template matching between templates learned from at least one original scene and templates learned from at least one current scene with motion removed, wherein said at least current scene with motion removed comprises a motion-removed current scene; employ said changes measured in said field of view to adjust data indicative of at least one region of interest for vision-based processing thereof if said changes measured are above a pre-determined threshold so that an impact of said changes with respect to said field of view to performance is minimized; apply diagnostics with respect to said field of view without compensation to assist in remotely repositioning a camera associated with said field of view back to said at least one original scene, wherein each of said templates comprise at least one M×
N sub-image derived from said at least one original scene and said at least one current scene with said motion removed and wherein said template matching is based on a normalized cross-correlation value as a similarity metric, wherein at run-time each image template among said templates slides against said motion-removed current scene and a location is determined, which yields a highest normalized cross-correlation value, said normalized cross-correlation value comprising said highest normalized cross correlation value.
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Specification