An electronic device includes a display, a memory and a processor. The memory includes instructions for causing the processor to, when generating a video, receive a video signal including an object to obtain a plurality of frame images having a first size, estimate a movement trajectory of the object included in the plurality of frame images, stitch together frame images in which overlapping portions of the video signal are arranged to overlap according to the movement trajectory of the object to generate a stitched image having a second size larger than the first size; and store the generated stitched image and the plurality of frame images as a video file.

A plurality of tracking cameras is pointed towards a routine hovering area of an in-the-field sports participant who routinely hovers about that area. Spots within the hovering area are registered relative to a predetermined multi-dimensional coordinates reference frame (e.g., Xw, Yw, Zw, Tw) such that two-dimensional coordinates of 2D images captured by the tracking cameras can be converted to multi-dimensional coordinates of the reference frame. A body part recognizing unit recognizes 2D locations of a specific body part in the 2D captured images and a mapping unit maps them into the multi-dimensional coordinates of the reference frame. A multi-dimensional curve generator then generates a multi-dimensional motion curve describing motion of the body part based on the mapped coordinates (e.g., Xw, Yw, Zw, Tw). The generated multi-dimensional motion curve is used to discover cross correlations between play action motions of the in-the-field sports participant and real-world sports results.

Embodiments of the disclosure provide a system and method for determining a trajectory of a subject. The method can include acquiring motion data of the subject to which the mobile device is attached; determining a motion status of the subject based on the motion data; and determining the trajectory based on the motion data using a trajectory model corresponding to the motion status.

An augmented reality system is provided for use with a medical imaging scanner. The AR system obtains a digital image from a camera, and identifies a pose of a gantry of the medical imaging scanner based on content of the digital image. The gantry includes a movable C-arm supporting an imaging signal transmitter and a detector panel that are movable along an arc relative to a station. A range of motion of the movable C-arm along the arc is determined based on the pose. A graphical object is generated based on the range of motion and the pose, and is provided to a display device for display as an overlay relative to the medical imaging scanner.

Embodiments are directed to calibrating multi-view triangulation systems that perceive surfaces and objects based on reflections of one or more scanned laser beams that are continuously sensed by two or more sensors. In addition to sampling and triangulating points from a spline formed by an unbroken line trajectory of a laser beam, the calibration system samples and triangulates a corresponding velocity vector. Iterative reduction is performed on velocity vectors instead of points or splines. The velocity vector includes directions and magnitudes along a trajectory of a scanning laser beam which are used to determine the actual velocities. Translation and rotation vectors are based on the velocity vectors for matching trajectories determined for two or more sensors having offset physical positions, which are used to calibrate sensor offset errors associated with the matching trajectories provided to a modeling engine.

An image processing apparatus comprising, a tracking unit configured to detect an object and track the object in images to be processed, the images being sequential with respect to time, a determining unit configured to determine a stay time for which the object stays, on the basis of a result of the tracking, and an associating unit configured to specify, on the basis of the result of the tracking, one predetermined location from one or more predetermined locations included in the images to be processed, and associate the specified one predetermined location with the stay time.

A system includes a processor and a memory. The memory stores instructions executable by the processor to receive an image from a stationary camera. The memory stores instructions to determine location coordinates of an object identified in the image based on location coordinates specified for the image. The memory stores instructions to operate a vehicle based on the object location coordinates.

Systems, computer-implemented methods, and non-transitory machine-readable storage media are provided for detecting recapture attacks of images. One method comprises extracting one or more features from an image captured by a device; applying the one or more features as input to a trained machine learning model, wherein the trained machine learning model outputs a first score based on the extracted features; obtaining metadata of the image; performing a statistical analysis of the metadata of the image; generating a second score based on the statistical analysis of the metadata of the image; and generating a probability that the image is a recapture of an original image based on the first score and the second score.

A method for measuring the motion response of a dummy in a crash test comprises: acquiring images of a measurement mark by a camera during the crash test, wherein the measurement mark is fixed on a part to be measured of the dummy, and the dummy is set in association with a preset platform; determining first coordinate positions of the measurement mark in the images; determining corresponding second coordinate positions of the first coordinate positions in a static coordinate system according to a preset conversion relationship, wherein the X-axis of the static coordinate system is parallel to the motion direction of the preset platform, the Y-axis of the static coordinate system is perpendicular to the motion direction of the preset platform; and determining a motion response trajectory of the part to be measured according to an initial position of the part to be measured and the second coordinate positions.

The present disclosure realizes a configuration capable of accurately displaying a flight path of a drone on an actually captured image of the drone. The configuration includes a data processing unit that displays a moving path of a moving device such as a drone on a display unit that displays a camera-capturing image of the moving device. The data processing unit generates a coordinate conversion matrix for performing coordinate conversion processing of converting position information according to a first coordinate system, for example, the NED coordinate system indicating the moving path of the moving device into a second coordinate system, for example, the camera coordinate system capable of specifying a pixel position of a display image on the display unit and outputs, to the display unit, the moving path having position information according to the camera coordinate system generated by coordinate conversion processing to which the generated coordinate conversion matrix is applied.