Abstract: The present disclosure provides for a method, device, and computer-readable storage medium for performing a method for discerning a vehicle at an access control point. The method including obtaining a video sequence of the access control point; detecting an object of interest from the video sequence; tracking the object from the video sequence to obtain tracked-object data; classifying the object to obtain classified-object data; determining that the object is a vehicle based on the classified-object data; and determining that the vehicle is present in a predetermined detection zone based on the tracked-object data.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for virtual inductance loop technology. In one aspect, a method includes calibrating, using calibration parameters, cameras directed towards a scene, obtaining, by the cameras, images corresponding to the scene, identifying reference structures in the scene, and determining, based on the reference structures and the images, locations in the scene for generating virtual inductance loop lines in the scene. The method also includes generating the virtual inductance loop lines to be imposed on the images, comparing the virtual inductance loop lines to determine one or more offsets, and determining, based on the offsets, characteristics of the scene.

Abstract: The present disclosure provides for a method, device, and computer-readable storage medium for performing a method for discerning a vehicle at an access control point. The method including obtaining a video sequence of the access control point; detecting an object of interest from the video sequence; tracking the object from the video sequence to obtain tracked-object data; classifying the object to obtain classified-object data; determining that the object is a vehicle based on the classified-object data; and determining that the vehicle is present in a predetermined detection zone based on the tracked-object data.

Abstract: The present disclosure provides for a method, device, and computer-readable storage medium for performing a method for discerning a vehicle at an access control point. The method including obtaining a video sequence of the access control point; detecting an object of interest from the video sequence; tracking the object from the video sequence to obtain tracked-object data; classifying the object to obtain classified-object data; determining that the object is a vehicle based on the classified-object data; and determining that the vehicle is present in a predetermined detection zone based on the tracked-object data.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for virtual inductance loop technology. In one aspect, a method includes calibrating, using calibration parameters, cameras directed towards a scene, obtaining, by the cameras, images corresponding to the scene, identifying reference structures in the scene, and determining, based on the reference structures and the images, locations in the scene for generating virtual inductance loop lines in the scene. The method also includes generating the virtual inductance loop lines to be imposed on the images, comparing the virtual inductance loop lines to determine one or more offsets, and determining, based on the offsets, characteristics of the scene.

Abstract: The present disclosure provides for a method, device, and computer-readable storage medium for performing a method for discerning a vehicle at an access control point. The method including obtaining a video sequence of the access control point; detecting an object of interest from the video sequence; tracking the object from the video sequence to obtain tracked-object data; classifying the object to obtain classified-object data; determining that the object is a vehicle based on the classified-object data; and determining that the vehicle is present in a predetermined detection zone based on the tracked-object data.

Abstract: A method is provided for augmenting video feed obtained by a camera of a aerial vehicle to a user interface. The method can include obtaining a sequence of video images with or without corresponding sensor metadata from the aerial vehicle; obtaining supplemental data based on the sequence of video images and the sensor metadata; correcting an error in the sensor metadata using a reconstruction error minimization technique; creating a geographically-referenced scene model based on a virtual sensor coordinate system that is registered to the sequence of video images; overlaying the supplemental information onto the geographically-referenced scene model by rendering geo-registered data from a 3D perspective that matches a corrected camera model; creating a video stream of a virtual representation from the scene from the perspective of the camera based on the overlaying; and providing the video stream to a UI to be render onto a display.

Abstract: The present disclosure provides for a method, device, and computer-readable storage medium for performing a method for discerning a vehicle at an access control point. The method including obtaining a video sequence of the access control point; detecting an object of interest from the video sequence; tracking the object from the video sequence to obtain tracked-object data; classifying the object to obtain classified-object data; determining that the object is a vehicle based on the classified-object data; and determining that the vehicle is present in a predetermined detection zone based on the tracked-object data.

Abstract: The present disclosure provides for a method, device, and computer-readable storage medium for performing a method for discerning a vehicle at an access control point. The method including obtaining a video sequence of the access control point; detecting an object of interest from the video sequence; tracking the object from the video sequence to obtain tracked-object data; classifying the object to obtain classified-object data; determining that the object is a vehicle based on the classified-object data; and determining that the vehicle is present in a predetermined detection zone based on the tracked-object data.

Abstract: The present disclosure provides for a method, device, and computer-readable storage medium for performing a method for discerning a vehicle at an access control point. The method including obtaining a video sequence of the access control point; detecting an object of interest from the video sequence; tracking the object from the video sequence to obtain tracked-object data; classifying the object to obtain classified-object data; determining that the object is a vehicle based on the classified-object data; and determining that the vehicle is present in a predetermined detection zone based on the tracked-object data.

Abstract: A method is provided for augmenting video feed obtained by a camera of a aerial vehicle to a user interface. The method can include obtaining a sequence of video images with or without corresponding sensor metadata from the aerial vehicle; obtaining supplemental data based on the sequence of video images and the sensor metadata; correcting an error in the sensor metadata using a reconstruction error minimization technique; creating a geographically-referenced scene model based on a virtual sensor coordinate system that is registered to the sequence of video images; overlaying the supplemental information onto the geographically-referenced scene model by rendering geo-registered data from a 3D perspective that matches a corrected camera model; creating a video stream of a virtual representation from the scene from the perspective of the camera based on the overlaying; and providing the video stream to a UI to be render onto a display.

Abstract: The present disclosure provides for a method, device, and computer-readable storage medium for performing a method for discerning a vehicle at an access control point. The method including obtaining a video sequence of the access control point; detecting an object of interest from the video sequence; tracking the object from the video sequence to obtain tracked-object data; classifying the object to obtain classified-object data; determining that the object is a vehicle based on the classified-object data; and determining that the vehicle is present in a predetermined detection zone based on the tracked-object data.