A firearm system includes a firearm and a computer. Electronics in the firearm determine data that includes a pathway between different points of aim of the firearm as the firearm moves. The computer receives this data and builds an image of the pathway between the different points of aim of the firearm.

A method of determining geo-reference data for a portion of a measurement area includes providing a monitoring assembly comprising a ground station, providing an imaging assembly comprising an imaging device with a lens operably coupled to an aerial device, hovering the aerial device over a measurement area, capturing at least one image of the measurement area within the imaging device, transmitting the at least one image to the ground station using a data transmitting assembly, and scaling the at least one image to determine the geo-reference data for the portion of the measurement area by calculating a size of a field-of-view (FOV) of the lens based on a distance between the imaging device and the measurement area.

An apparatus for determining wind speed includes an image capture device, a memory, and a computer-readable medium. The image capture device captures video and the memory stores the video. The computer-readable medium includes a computer program product stored thereon, and the computer program product is configured to determine a wind speed in the scene based on analysis of atmospheric turbulence occurring in the video. The method may include comparing a set of models to an analyzed video to determine the wind speed.

The present disclosure provides a target tracking method to be executed by a computing device, including: generating an optical flow image in accordance with a series of event data from a dynamic vision sensor, each event being triggered by movement of a target object relative to the dynamic vision sensor; determining a movement speed and a movement direction of at least one target object in a current image frame in accordance with the optical flow image; predicting a position of a corresponding target object in a next image frame in accordance with the movement direction and the movement speed; and when a predicted position is within a range of a field of view, taking the corresponding target object as a to-be-tracked target. The present disclosure further provides a computing device.

An augmented reality system includes a global navigation satellite system module adapted to output position data, an orientation measurement module adapted to output orientation data, an augmented reality module, at least one AR-client having a camera and a display. The augmented reality module is adapted to determine a position and orientation of the camera of the at least one AR-client based on the position data and orientation data, calculating screen positions of at least one AR object based on the position and orientation of the camera of the at least one AR-client to create at least one AR-overlay, transmitting the at least one AR overlay to at least one AR-client, and the AR-client is adapted to merging the at least one AR-overlay with a picture received from the camera of the at least one AR-client to provide an AR-image, and displaying the AR-image on the display.

Discussed herein are architectures and techniques for improving execution or training of machine learning techniques. A method can include receiving a request for image data, the request indicating an analysis task to be performed using the requested image data, determining a minimum image quality score for performing the analysis task, issuing a request for image data associated with an image quality at last equal to, or greater than, the determined minimum image quality score, receiving, in response to the request, image data with an image quality score greater than, or equal to, the determined minimum image quality score, and providing the received image data to (a) a machine learning (ML) model executor to perform the image analysis task or (b) an ML model trainer that trains the ML model to perform the image analysis task.

A camera is arranged on a transmitter or receiver mount configured to provide a transmitter or receiver with a field of regard. Image data of the field of regard is captured by the camera. A location of an obscuration within the field of regard from the image data is determined from the image data. A map of obscurations within the field of regard is generated based upon the image data and the location of the obscuration within the field of regard.

Systems, methods, and apparatus for detecting UAVs in an RF environment are disclosed. An apparatus is constructed and configured for network communication with at least one camera. The at least one camera captures images of the RF environment and transmits video data to the apparatus. The apparatus receives RF data and generates FFT data based on the RF data, identifies at least one signal based on a first derivative and a second derivative of the FFT data, measures a direction from which the at least one signal is transmitted, analyzes the video data. The apparatus then identifies at least one UAV to which the at least one signal is related based on the analyzed video data, the RF data, and the direction from which the at least one signal is transmitted, and controls the at least one camera based on the analyzed video data.

The present invention relates to a computer-implemented method for targeting missiles, to a corresponding computer program, to a corresponding computer-readable medium and to a corresponding data processing device, as well as to a missile.

A missile controller guides a missile along a flight path to a stationary or moving target object. The missile controller has at least one side-looking sensor, configured to record surroundings data and has a field of view aligned transverse to the longitudinal axis of the missile, and a control unit having a reception unit for receiving target object data regarding the target object. The target object data containing position data, orientation data and/or speed data of the target object. The control unit is configured to set the orientation of the missile during the guidance at least partly based on the received target object data such that the target object is located in the field of view of the side-looking sensor at least in sections of a final guidance phase.