Abstract:
A method, system, and apparatus for vehicle occupancy detection comprises collecting image data of a vehicle, creating a first value according to a plurality of characteristics of a driver position of the vehicle, and then creating at least one other value according to a plurality of characteristics of at least one other candidate occupant position in the vehicle. The characteristics of the driver position of the vehicle and candidate occupant position of the vehicle are compared in order to determine the vehicle occupancy.
Abstract:
A method, non-transitory computer readable medium, and apparatus for detecting an object in an image are disclosed. For example, the method receives the image, calculates a score for each one of a plurality of locations in the image, performs a box plot of the score of the each one of the plurality of locations of the image, identifies an outlier score that falls outside of the box plot, determines that a distance ratio of the outlier score is less than a predefined distance ratio and detects the object in a location of the plurality of locations of the image corresponding to the outlier score.
Abstract:
A method for processing an image of a scene of interest includes receiving an original target image of a scene of interest at an image processing device from an image source device, the original target image exhibiting shadowing effects associated with the scene of interest when the original target image was captured, the original target image comprising a plurality of elements and representing an instantaneous state for the scene of interest, pre-processing the original target image using a modification identification algorithm to identify elements of the original target image to be modified, and generating a copy mask with a mask region representing the elements to be modified and a non-mask region representing other elements of the original target image. An image processing device for processing an image of a scene of interest and a non-transitory computer-readable medium are also provided.
Abstract:
A computer-implemented method, system, and computer-readable medium is disclosed for determining a sequence order for vehicles in one or more image frames from an operational video, the operational video acquired from a fixed video camera comprising a field of view associated with a vehicle merge area where upstream traffic from a first lane and upstream traffic from a second lane merge to a single lane. The method can include obtaining operational video from a fixed video camera; detecting, within a region of interest (ROI) of the one or more image frames from the operational video, a first area and a second area in the vehicle merge area using a trained classifier that is trained to detect the first area and the second area; and determining the sequence order of the vehicles based on the first area and the second area that are detected.
Abstract:
Methods, systems and processor-readable media for providing a license plate overlay decal with an infrared readable annotation mark for an optical character recognition and segmentation. The annotation mark with respect to character image of a license plate can be designed by training an ALPR engine to improve automatic license plate recognition performance. A plate overlay decal can be rendered with the annotation mark and attached to a license plate. The annotation mark can also be directly placed on the license plate when the license plate is rendered. The annotation mark is visible when illuminated by an infrared light and the license plate appears normal in visible light. The annotation mark enables an ALPR imaging system to obtain more information for each character and utilize the information to improve conclusion accuracy.
Abstract:
A system and method to capture an image of an oncoming target vehicle and localize the windshield of the target vehicle. Upon capturing an image, it is then analyzed to detect certain features of the target vehicle. Based on geometrical relationships of the detected features, the area of the image containing the windshield of the vehicle can then be identified and localized for downstream processing.
Abstract:
Methods, systems, and processor-readable media for detecting the side window of a vehicle. A spatial probability map can be calculated, which includes data indicative of likely side window locations of a vehicle in an image. A side window detector can be run with respect to the image of the vehicle to determine detection scores. The detection scores can be weighted based on the spatial probability map. A detected region of interest can be extracted from the image as extracted image patch. An image classification can then be performed with respect to the extracted patch to provide a classification that indicates whether or not a passenger is in the vehicle or no-passenger is in the vehicle.
Abstract:
Methods and systems for continuously monitoring the gaze direction of a driver of a vehicle over time. Video is received, which is captured by a camera associated with, for example, a mobile device within a vehicle, the camera and/or mobile device mounted facing the driver of the vehicle. Frames can then be extracted from the video. A facial region can then be detected, which corresponds to the face of the driver within the extracted frames. Features descriptors can then be computed from the facial region. A gaze classifier derived from the vehicle, the driver, and the camera can then be applied, wherein the gaze classifier receives the feature descriptors as inputs and outputs at least one label corresponding to one or more predefined finite number of gaze classes to identify the gaze direction of the driver of the vehicle.
Abstract:
Methods, systems, and processor-readable media for training data augmentation. A source domain and a target domain are provided, and thereafter an operation is performed to augment data in the source domain with transformations utilizing characteristics learned from the target domain. The augmented data is then used to improve image classification accuracy in a new domain.
Abstract:
Methods, systems, and processor-readable media for training data augmentation. A source domain and a target domain are provided, and thereafter an operation is performed to augment data in the source domain with transformations utilizing characteristics learned from the target domain. The augmented data is then used to improve image classification accuracy in a new domain.