Vehicle detection method and system including irrelevant window elimination and/or window score degradation
First Claim
1. A computer implemented method of detecting one or more vehicles in a video frame acquired from a fixed parking occupancy video camera including a field of view associated with a vehicle parking region, the computer implemented method comprising the steps of:
- a) capturing a video frame from the fixed parking occupancy video camera, the video frame including a ROI (Region of Interest) oriented by an orientation angle relative to an orientation of an image plane associated with the captured video frame, the ROI including one or more parking spaces of the vehicle parking region;
b) performing a sliding window-based search for one or more vehicles within the ROI, the sliding window-based search extracting one or more features associated with each of a plurality of candidate search windows representing a set of windows from which one or more mutually exclusive object bounding boxes are selected, wherein each selected mutually exclusive object bounding box is associated with a vehicle, and wherein the vehicle is not associated with any of the other mutually exclusive object bounding boxes;
c) accessing a classifier to classify each candidate search window as including a vehicle or not including a vehicle, wherein the classifier generates a score for each candidate window based on one or more features associated with each candidate search window, the score of each candidate search window degraded as a function of at least one of a fixed or an adaptive aspect ratio associated with each candidate search window; and
d) suppressing one or more overlapping classified candidate search windows including a common vehicle having a classification score below a predetermined threshold, wherein overlapping candidate search windows are eliminated from detecting the common vehicle,wherein the classified candidate search windows are limited to candidate search windows of one or more predefined window shapes to exclude search windows limited to a partial detection of a vehicle, and candidate search windows which are not suppressed are considered to be the one or more mutually exclusive object bounding boxes representative of the one or more vehicles detected in the video frame.
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Abstract
This disclosure provides vehicle detection methods and systems including irrelevant search window elimination and/or window score degradation. According to one exemplary embodiment, provided is a method of detecting one or more parked vehicles in a video frame, wherein candidate search windows are limited to one or more predefined window shapes. According to another exemplary embodiment, the method includes degrading a classification score of a candidate search window based on aspect ratio, window overlap area and/or a global maximal classification.
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Citations
25 Claims
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1. A computer implemented method of detecting one or more vehicles in a video frame acquired from a fixed parking occupancy video camera including a field of view associated with a vehicle parking region, the computer implemented method comprising the steps of:
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a) capturing a video frame from the fixed parking occupancy video camera, the video frame including a ROI (Region of Interest) oriented by an orientation angle relative to an orientation of an image plane associated with the captured video frame, the ROI including one or more parking spaces of the vehicle parking region; b) performing a sliding window-based search for one or more vehicles within the ROI, the sliding window-based search extracting one or more features associated with each of a plurality of candidate search windows representing a set of windows from which one or more mutually exclusive object bounding boxes are selected, wherein each selected mutually exclusive object bounding box is associated with a vehicle, and wherein the vehicle is not associated with any of the other mutually exclusive object bounding boxes; c) accessing a classifier to classify each candidate search window as including a vehicle or not including a vehicle, wherein the classifier generates a score for each candidate window based on one or more features associated with each candidate search window, the score of each candidate search window degraded as a function of at least one of a fixed or an adaptive aspect ratio associated with each candidate search window; and d) suppressing one or more overlapping classified candidate search windows including a common vehicle having a classification score below a predetermined threshold, wherein overlapping candidate search windows are eliminated from detecting the common vehicle, wherein the classified candidate search windows are limited to candidate search windows of one or more predefined window shapes to exclude search windows limited to a partial detection of a vehicle, and candidate search windows which are not suppressed are considered to be the one or more mutually exclusive object bounding boxes representative of the one or more vehicles detected in the video frame. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer implemented method of detecting one or more vehicles in a video frame acquired from a fixed parking occupancy video camera including a field of view associated with a vehicle parking region, the method comprising:
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a) capturing a video frame from the fixed parking occupancy video, the video frame including a ROI (Region of Interest) oriented by an orientation angle relative to an orientation of an image plane associated with the captured video frame, the ROI including one or more parking spaces of the vehicle parking region; b) performing a sliding window-based search for one or more vehicles within the ROI, the sliding window-based search extracting one or more features associated with each of a plurality of candidate search windows representing a set of windows from which object bounding boxes are selected, wherein each selected object bounding box is associated with a vehicle, and wherein the vehicle is not associated with any of the other object bounding boxes; c1) accessing a classifier to score each candidate search window with a classification score calculated by the classifier indicating a probability of candidate search window includes a vehicle relative to a plurality of training images used to train the classifier; c2) degrading the classification score of one or more classified overlapping search windows including a common vehicle, the classification score degraded by an amount that is a function of an overlap area of the overlapping search windows and a relative size of each of the overlapping windows; and d) performing a NMS (Non-Maximal Suppression) process to suppress any overlapping classified candidate search window with a classification score below a predetermined threshold, wherein classified candidate search windows which are not suppressed are considered to be object bounding boxes representative of the one or more vehicles detected in the video frame. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A vehicle detection system associated with a vehicle parking region, the vehicle detection system comprising:
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a parking occupancy video camera directed towards the vehicle parking region; and a controller operatively associated with the parking occupancy video camera, the controller configured to execute computer instructions to perform a process of detecting a vehicle in a video frame including; a) capturing a video frame from the fixed parking occupancy video, the video frame including a ROI (Region of Interest) oriented by an orientation angle relative to an orientation of an image plane associated with the captured video frame, the ROI including one or more parking spaces of the vehicle parking region; b) performing a sliding window-based search for one or more vehicles within the ROI, the sliding window-based search extracting one or more features associated with each of a plurality of candidate search windows representing a set of windows from which object bounding boxes are selected, wherein each selected object bounding box is associated with a vehicle, and wherein the vehicle is not associated with any of the other object bounding boxes; c1) accessing a classifier to score each candidate search window with a classification score calculated by the classifier indicating a probability of candidate search window includes a vehicle relative to a plurality of training images used to train the classifier; c2) degrading the classification score of one or more classified overlapping search windows including a common vehicle, the classification score degraded by an amount that is a function of an overlap area of the overlapping search windows and a relative size of each of the overlapping windows; and d) performing a NMS (Non-Maximal Suppression) process to suppress any overlapping classified candidate search window with a classification score below a predetermined threshold, wherein classified candidate search windows which are not suppressed are considered to be object bounding boxes representative of the one or more vehicles detected in the video frame. - View Dependent Claims (22, 23, 24, 25)
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Specification