Abstract:
A method for determining parking availability includes receiving video data from a sequence of frames taken from an image capture device monitoring a parking area. The method includes detecting at least one object located in the parking area. The method includes determining boundaries of the parking area. The boundaries include at least an inner boundary relative to the image capture device and an outer boundary relative to the image capture device. The outer boundary is substantially parallel to the inner boundary. The method further includes computing a length of at least one of the object and a space between objects using an object pixel for each of the inner and outer boundaries. Using the computed length, The method includes determining a parking availability in the parking area. The method includes outputting a notice of the parking availability to a user.
Abstract:
This disclosure provides methods and systems for form a trajectory of a moving vehicle captured with an image capturing device. According to one exemplary embodiment, a method forms a trajectory of a moving vehicle and determines if the vehicle is moving in one of a permitted manner and an unpermitted manner relative to the appropriate motor vehicle lane restriction laws and/or regulations.
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.
Abstract:
A computer-implemented method, system, and computer-readable medium is disclosed for determining an estimated available parking distance for a vehicle via vehicle side detection in one or more image frames from an operational video. The operational video can be acquired from a fixed parking occupancy video camera and can include a field of view associated with a parking region. The method can include obtaining operational video from a fixed parking occupancy video camera; detecting, within a region of interest (ROI) of the one or more image frames from the operational video, a side of one or more vehicles parked in a parking region facing a traffic lane using a trained classifier that is trained to detect the side of the one or more vehicles; and determining an estimated available parking distance based on the side of the one or more vehicles that are detected.
Abstract:
Multi-stage vehicle detection systems and methods for side-by-side drive-thru configurations. One or more video cameras (or an image-capturing unit) can be employed for capturing video of a drive-thru of interest in a monitored area. A group of modules can be provided, which define multiple virtual detection loops in the video and sequentially perform classification with respect to each virtual detection loops among the multiple virtual detection loops, starting from a virtual detection loop closest to an order point, and when a vehicle having a car ID is sitting in a drive-thru queue, so as to improve vehicle detection performance in automated post-merge sequencing.
Abstract:
Methods, systems, and processor-readable media for the detection and classification of license plates. In an example embodiment, an image of a vehicle can be captured with an image-capturing unit. A license plate region can then be located in the captured image of the vehicle by extracting a set of candidate regions from the image utilizing a weak classifier. A set of candidate regions can be ranked utilizing a secondary strong classifier. The captured image can then be classified according to a confidence driven classification based on classification criteria determined by the weak classifier and the secondary strong classifier.
Abstract:
Methods and systems for recognizing a license plate character. Synthetic license plate character images are generated for a target jurisdiction. A limited set of license plate images can be captured for a target jurisdiction utilizing an image-capturing unit. The license plate images are then segmented into license plate character images for the target jurisdiction. The license plate character images collected for the target jurisdiction can be manually labeled. A domain adaptation technique can be utilized to reduce the divergence between synthetically generated and manually labeled target jurisdiction image sets. Additionally, OCR classifiers are trained utilizing the images after the domain adaptation method has been applied. One or more input license plate character images can then be received from the target jurisdiction. Finally, the trained OCR classifier can be employed to determine the most likely labeling for the character image and a confidence associated with the label.
Abstract:
A system and method for monitoring parking and identifying vehicles by monitoring a parking region based on video data of the parking region received from a video camera, detecting a parking event associated with a vehicle in the parking region, adjusting a view of the video camera based on the parking event, physically tracking the vehicle using the video camera, capturing an image of a license plate of the vehicle, and resuming monitoring the parking region after capturing the image of the license plate.
Abstract:
Provided is a method and system for efficient localization in still images. According to one exemplary method, a sliding window-based 2-D (Dimensional) space search is performed to detect a parked vehicle in a video frame acquired from a fixed parking occupancy video camera including a field of view associated with a parking region.
Abstract:
A system and method for detecting electronic device use by a driver of a vehicle including acquiring an image including a vehicle from an associated image capture device positioned to view oncoming traffic, locating a windshield region of the vehicle in the captured image, processing pixels of the windshield region of the image for computing a feature vector describing the windshield region of the vehicle, applying the feature vector to a classifier for classifying the image into respective classes including at least classes for candidate electronic device use and candidate electronic device non-use, and outputting the classification.