Video/vision based access control method and system for parking occupancy determination, which is robust against camera shake
First Claim
1. A method for parking occupancy determination, said method comprising:
- acquiring video of an entrance to a parking lot utilizing at least one video camera focusing on a computer vision-based region of interest for vehicle validation and a video-based region of interest for motion detecting and tracking;
video processing said video via at least one classifier trained with data collected from said parking lot and to take into account potential camera shake disturbances to generate video output data thereof, wherein said at least one classifier comprises at least one computer vision-based image content classifier;
analyzing said video output data for parking lot occupancy data, wherein an impact of camera shake with respect to said at least one video camera is minimized to determine parking lot occupancy;
determining an access type with respect to said parking lot based on said parking lot occupancy data, after analyzing said video output data for said parking lot occupancy data;
configuring said at least one classifier to comprise said computer vision-based image content classifier that performs image content classification for the computer vision-based region of interest and assists in object tracking with respect to said video-based region of interest;
applying distortions that simulate camera shake effects with respect to at least one image frame;
cropping said at least one image frame at an original region of interest after said applying said distortions that simulate said camera shake effects with respect to said at least one image frame;
incorporating said potential camera shake disturbances into training of said at least one classifier used for computer vision-based processing for said computer vision-based region of interest for vehicle validation and used for trajectory smoothing said video output data to remove an impact of high-frequency components during said camera shake disturbances;
measuring changes in a field of view of said video using template matching between templates derived from at least one original scene and at least one current scene with motion removed; and
employing said changes measured in said field of view to adjust data indicative of at least one region of interest for computer vision-based processing thereof if said changes measured are above a pre-determined threshold so that an impact of said changes with respect so said field of view to performance is minimized and determine said parking lot occupancy.
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Accused Products
Abstract
Methods and systems for parking lot occupancy determination. Video of an entrance to a parking lot (or other facility) can be acquired utilizing one or more video cameras focusing on a pre-defined vision-based region of interest and a pre-defined video-based region of interest. The video can be video processed via a classifier that is pre-trained to take into account potential camera shake disturbances to generate video output data thereof. The video output data can then be trajectory smoothed. The video output data (following trajectory smoothing) can then be analyzed for parking lot occupancy data such that the impact of camera shake with respect to the video camera(s) is minimized to determine parking lot occupancy.
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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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acquiring video of an entrance to a parking lot utilizing at least one video camera focusing on a computer vision-based region of interest for vehicle validation and a video-based region of interest for motion detecting and tracking; video processing said video via at least one classifier trained with data collected from said parking lot and to take into account potential camera shake disturbances to generate video output data thereof, wherein said at least one classifier comprises at least one computer vision-based image content classifier; analyzing said video output data for parking lot occupancy data, wherein an impact of camera shake with respect to said at least one video camera is minimized to determine parking lot occupancy; determining an access type with respect to said parking lot based on said parking lot occupancy data, after analyzing said video output data for said parking lot occupancy data; configuring said at least one classifier to comprise said computer vision-based image content classifier that performs image content classification for the computer vision-based region of interest and assists in object tracking with respect to said video-based region of interest; applying distortions that simulate camera shake effects with respect to at least one image frame; cropping said at least one image frame at an original region of interest after said applying said distortions that simulate said camera shake effects with respect to said at least one image frame; incorporating said potential camera shake disturbances into training of said at least one classifier used for computer vision-based processing for said computer vision-based region of interest for vehicle validation and used for trajectory smoothing said video output data to remove an impact of high-frequency components during said camera shake disturbances; measuring changes in a field of view of said video using template matching between templates derived from at least one original scene and at least one current scene with motion removed; and employing said changes measured in said field of view to adjust data indicative of at least one region of interest for computer vision-based processing thereof if said changes measured are above a pre-determined threshold so that an impact of said changes with respect so said field of view to performance is minimized and determine said parking lot occupancy. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A system for parking occupancy determination, said system comprising:
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a processor; and a 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; acquiring video of an entrance to a parking lot utilizing at least one video camera focusing on a computer vision-based region of interest for vehicle validation and a video-based region of interest for motion detecting and tracking; video processing said video via at least one classifier trained with data collected from said parking lot and to take into account potential camera shake disturbances to generate video output data thereof, wherein said at least one classifier comprises at least one computer vision-based image content classifier; tracking at least one vehicle within said video of said entrance to said parking lot utilizing said at least one classifier; analyzing said video output data for parking lot occupancy data, wherein an impact of camera shake with respect to said at least one video camera is minimized to determine parking lot occupancy; determining an access type with respect to said parking lot based on said parking lot occupancy data, after analyzing said video output data for said parking lot occupancy data; incorporating said potential camera shake level considerations into training of said at least one classifier used for computer vision-based processing for said computer vision-based region of interest for vehicle validation and used for trajectory smoothing said video output data to remove an impact of high-frequency components in said camera shake; video processing said video at said pre-defined video-based region of interest for motion detection and tracking, if motion is detected within said pre-defined vision-based region of interest; analyzing said video for a vehicle trajectory of said at least one vehicle to determine if said at least one vehicle is entering or exiting said parking lot; training said at least one classifier based on pulled samples indicative of camera shake in scone to include said potential camera shake disturbances into said at least one classifier; deriving new pixel locations with respect to said computer vision-based region of interest for said vehicle validation if a determined amount exceeds a pre-determined threshold, and if said amount does not exceed said pre-determined threshold, leave pixel locations unchanged with respect to said computer vision-based region of interest for vehicle validation; wherein said computer vision-based region of interest for vehicle validation is contained within said video-based region of interest for motion detecting and tracking; randomly moving, rotating, scaling, and warping said computer vision-based region of interest; and cropping said training samples to capture said samples indicative of said camera shake. - View Dependent Claims (13, 14, 15, 16)
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Specification