Photographs can sometimes be altered or changed in order to create photographs which appear to be of a scene which never took place, or did not take place at the place and time when the photograph is purported to have been taken. One way of circumventing known systems to detect this sort of falsified image is to take a photograph of a printed altered image. The present invention is a method of detecting such photographs of photographs by comparing two photographs of the same seen taken at the same time, with different exposures.

The invention relates to a system and method for determining a movable object's three dimensional position, comprising an attachable camera, attached to the object, and configured to capture an image containing representations of visual features that are spaced apart from the camera, means for storing the visual features, the features comprising a set of landmarks, containing position information of the corresponding visual feature, and detecting the positions the visual features in the captured image as mage positions of the visual features; estimate camera orientation; define an image plane, of the camera orientation; project positions of the visual features stored in the 3D model onto the virtual image plane creating positions of the visual features; perform matching between the image positions and the projected visual features positions, Identifying image visual features; and determine the position of the object from the three-dimensional positions of the visual features identified in the matching process.

A computer-implemented method of determining a relative velocity between a vehicle and an object. The method includes receiving sensor data generated by one or more sensors of the vehicle configured to sense an environment following a scan pattern. The method also includes obtaining, based on the sensor data, a point cloud frame. The point cloud frame comprises a plurality of points of depth data and a time at which the depth data was captured. Additionally, the method includes selecting two or more points of the scan pattern that overlap the object. The selected points are located on or near a two-dimensional surface corresponding to the object, and the depth data for two or more of the selected points are captured at different times. The method includes calculating the relative velocity between the vehicle and the object based on the depth data and capture times associated with the selected points.

A computer-implemented method of determining relative velocity between a vehicle and an object. The method includes receiving sensor data generated by one or more sensors of the vehicle. The one or more sensors are configured to sense an environment through which the vehicle is moving by following a scan pattern comprising component scan lines. The method also includes obtaining, based on the sensor data and by one or more processors, two or more point cloud frames representative of the environment and tracking, by the one or more processors, a point cloud object across the two or more point cloud frames. Additionally, the method includes determining, based on the tracking and by the one or more processors, a relative velocity of the point cloud object and correcting, by the one or more processors, the point cloud object based on the relative velocity of the point cloud object.

A computer-implemented method of determining relative velocity between a vehicle and an object. The method includes receiving sensor data generated by one or more sensors of the vehicle. The one or more sensors are configured to sense an environment through which the vehicle is moving by following a scan pattern comprising component scan lines. The method includes obtaining, by one or more processors, a point cloud frame based on the sensor data and representative of the environment and identifying, by the one or more processors, a point cloud object within the point cloud frame. The method further includes determining, by the one or more processors, that the point cloud object is skewed relative to an expected configuration of the point cloud object, and determining, by the one or more processors, a relative velocity of the point cloud object by analyzing the skew of the object.

A computer-implemented method of detecting object distortion. The method includes receiving sensor data generated by one or more sensors of the vehicle. The one or more sensors are configured to sense an environment through which the vehicle is moving by following a scan pattern. The method also includes obtaining, based on the sensor data, a point cloud frame representative of the environment and identifying a point cloud object within the point cloud frame. Additionally, the method includes analyzing the point cloud object to identify a feature of the point cloud object that has an expected shape and comparing the feature of the point cloud object to the expected shape. The method also includes identifying that the point cloud object is distorted based on the feature of the point cloud object not matching the expected shape.

A computer-implemented method of determining relative velocity between a vehicle and an object. The method includes receiving sensor data generated by one or more sensors of the vehicle configured to sense an environment by following a scan pattern comprising component scan lines. The method includes obtaining, based on the sensor data, a point cloud frame. Additionally, the method includes identifying a first pixel and a second pixel that are co-located within a field of regard and overlap a point cloud object within the point cloud frame and calculating a difference between a depth associated with the first pixel and a depth associated with the second pixel. The method includes determining a relative velocity of the point cloud object by dividing the difference in depth data by a time difference between when the depth associated with the first pixel was sensed and the depth associated with the second pixel was sensed.

An automotive vehicle includes a sensor configured to detect features external to the vehicle, an HMI configured to signal an alert to an operator of the vehicle, and a controller. The controller is in communication with the sensor and the HMI, and is in communication with a non-transient computer-readable storage medium provided with a road furniture database. The road furniture database includes a plurality of items of road furniture having associated road furniture geolocations and road furniture classifications. The controller is configured to, in response to the vehicle being proximate a respective road furniture geolocation for a respective item of road furniture and the sensor not detecting the respective item of road furniture, control the HMI to signal an alert.

A computer-implemented method of determining a relative velocity between a vehicle and an object. The method includes receiving sensor data generated by one or more sensors of the vehicle configured to sense an environment following a scan pattern. The method also includes obtaining, based on the sensor data, a point cloud frame. The point cloud frame comprises a plurality of points of depth data and a time at which the depth data was captured. Additionally, the method includes selecting two or more points of the scan pattern that overlap the object. The selected points are located on or near a two-dimensional surface corresponding to the object, and the depth data for two or more of the selected points are captured at different times. The method includes calculating the relative velocity between the vehicle and the object based on the depth data and capture times associated with the selected points.

A computer-implemented method of determining relative velocity between a vehicle and an object. The method includes receiving sensor data generated by one or more sensors of the vehicle. The one or more sensors are configured to sense an environment through which the vehicle is moving by following a scan pattern comprising component scan lines. The method also includes obtaining, based on the sensor data and by one or more processors, two or more point cloud frames representative of the environment and tracking, by the one or more processors, a point cloud object across the two or more point cloud frames. Additionally, the method includes determining, based on the tracking and by the one or more processors, a relative velocity of the point cloud object and correcting, by the one or more processors, the point cloud object based on the relative velocity of the point cloud object.