Methods and system for automated in-field hierarchical training of a vehicle detection system
First Claim
Patent Images
1. A computer implemented method of detecting a vehicle in video, the video acquired from a fixed parking occupancy video camera including a field of view associated with a parking region, the method comprising:
- a) capturing video from the fixed parking occupancy video camera; and
b) performing a sliding window-based space search for a vehicle within the captured video, the sliding window-based space search extracting one or more features associated with each of a plurality of windows and accessing an operatively associated second classifier to classify each window as including a vehicle or not including a vehicle,wherein the second classifier is trained using high confidence training samples acquired from samples of video obtained from the fixed parking occupancy video camera operatively associated with a first classifier, the samples including positive (vehicle) samples of video and negative (non-vehicle) samples of video, andwherein the first classifier is trained with video captured from another fixed parking occupancy video camera including a different field of view associated with another parking region.
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Abstract
Disclosed are methods and systems for detecting one or more vehicles in video captured from a deployed video camera directed at a parking region. According to one exemplary embodiment, disclosed is a method of training a deployed classifier associated with the video camera, where a generic classifier is initially used to obtain high confidence training samples from the video camera, the high confidence training samples subsequently used to train the deployed classifier.
46 Citations
22 Claims
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1. A computer implemented method of detecting a vehicle in video, the video acquired from a fixed parking occupancy video camera including a field of view associated with a parking region, the method comprising:
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a) capturing video from the fixed parking occupancy video camera; and b) performing a sliding window-based space search for a vehicle within the captured video, the sliding window-based space search extracting one or more features associated with each of a plurality of windows and accessing an operatively associated second classifier to classify each window as including a vehicle or not including a vehicle, wherein the second classifier is trained using high confidence training samples acquired from samples of video obtained from the fixed parking occupancy video camera operatively associated with a first classifier, the samples including positive (vehicle) samples of video and negative (non-vehicle) samples of video, and wherein the first classifier is trained with video captured from another fixed parking occupancy video camera including a different field of view associated with another parking region. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer implemented method of detecting a video, the video acquired from a fixed parking occupancy video camera including a field of view associated with a parking region, the method comprising:
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a) capturing video from the fixed parking occupancy video camera; and b) performing a sliding window-based space search for a vehicle within the captured video, the sliding window-based space search extracting one or more features associated with each of a plurality of windows and accessing an operatively associated second classifier to classify each window as including a vehicle or not including a vehicle, wherein the second classifier is trained using high confidence training samples acquired from samples of video obtained from the fixed parking occupancy video camera operatively associated with a first classifier, the samples including positive (vehicle) samples of video and negative (non-vehicle) samples of video, and wherein the positive (vehicle) samples of video are associated with a sub-region of a video-frame, the sub-region related to a ROI (Region of Interest). - View Dependent Claims (11)
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12. A vehicle detection system associated with a parking region, the vehicle detection system comprising:
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a fixed parking occupancy video camera including a field of view associated with the parking region; and a controller operatively associated with the fixed parking occupancy video camera, the controller configured to execute computer instructions to perform a process of detecting a vehicle in video including; a) capturing video from the fixed parking occupancy video camera; and b) performing a sliding window-based space search for a vehicle within the captured video, the sliding window-based space search extracting one or more features associated with each of a plurality of windows and accessing a second classifier to classify each window as including a vehicle or not including a vehicle, wherein the second classifier is trained using high confidence training samples acquired from samples of video obtained from the parking occupancy video camera operatively associated with a first classifier, the samples including positive (vehicle) samples of video and negative (non-vehicle) samples of video, and wherein the first classifier is trained with video captured from another fixed parking occupancy video camera including a different field of view associated with another parking region. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. A vehicle detection system associated with a parking region, the vehicle detection system comprising:
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a fixed parking occupancy video camera including a field of view associated with the parking region; and a controller operatively associated with the fixed parking occupancy video camera, the controller configured to execute computer instructions to perform a process of detecting a vehicle in video including; a) capturing video from the fixed parking occupancy video camera; and b) performing a sliding window-based space search for a vehicle within the captured video, the sliding window-based space search extracting one or more features associated with each of a plurality of windows and accessing a second classifier to classify each window as including a vehicle or not including a vehicle, wherein the second classifier is trained using high confidence training samples acquired from samples of video obtained from the parking occupancy video camera operatively associated with a first classifier, the samples including positive (vehicle) samples of video and negative (non-vehicle) samples of video, and wherein the positive (vehicle) samples of video are associated with a sub-region of a video frame, the sub-region related to a ROI (Region of Interest).
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Specification