Provided are a device and method that calculate a predicted motion vector corresponding to a type and posture of a tracked subject, and generate a camera control signal necessary for capturing an image of a tracked subject. There are included a predicted subject motion vector calculation unit that detects a tracked subject of a previously designated type from a captured image input from an imaging unit and calculates a predicted motion vector corresponding to a type and posture of the detected tracked subject, and a camera control signal generation unit that generates, on the basis of the predicted motion vector calculated by the predicted subject motion vector calculation unit, a camera control signal for capturing an image of a tracked image of the tracked subject. By using a neural network or the like, the predicted subject motion vector calculation unit executes processing of detecting a tracked subject of a type designated from the captured image by a user, and predicted motion vector calculation processing.

A method (400) of capturing and processing electroluminescence (EL) images (1910) of a PV array (40) is disclosed herein. In a described embodiment, the method 400 includes controlling the aerial vehicle (20) to fly along a flight path to capture EL images (1910) of corresponding PV array subsections (512b) of the PV array (40), deriving respective image quality parameters from at least some of the captured EL images, dynamically adjusting a flight speed of the aerial vehicle along the flight path, based on the respective image quality parameters for capturing the EL images (1910) of the PV array subsections (512b), extracting a plurality of frames (1500) of the PV array subsection (512b) from the EL images (1910); determining a reference frame having a highest image quality of the PV array subsection (512b) from among the extracted frames (2100); performing image alignment of the extracted frames (2100) to the reference frame to generate image aligned frames (2130), and processing the image aligned frames (2130) to produce an enhanced image (2140) of the PV array subsection (512b) having a higher resolution than the reference frame. A system, image processing device, and aerial vehicle for the method thereof are also disclosed.

Provided is a measuring device for measuring the hardness of a rotor blade groove. This measuring device comprises: a hardness meter for measuring hardness; an actuator that presses the hardness meter to an object to be measured; a camera for capturing an image of a measurement range in the object to be measured by the hardness meter; a movement mechanism for moving the hardness meter and the camera to a desired position within the measurement range; and a fixing member for fixing the movement mechanism to the object to be measured.

A system and apparatus for automated image capturing, comprising a microcontroller, an image capturing device operatively coupled to the pair of guiding apparatus using a first electric rotary actuator, a rotary plate operatively mounted on a second electric rotary actuator. The pair of guiding apparatus and the first electric rotary actuator is actuated to cause change in position of the image capturing device relative to an object positioned on the rotary plate and second electric rotary actuator is actuated causing change in angle of orientation of the object positioned on the rotary plate. By varying lighting conditions and for different background images, plurality of images of object are captured using the image capturing device by actuating electro-mechanical components of the apparatus.

A zoom control method is provided, including: determining a midpoint of a connecting line of touch points located on both sides of an object to be close-up; determining a pixel vector formed from the midpoint of the connecting line to a center point of a screen; converting the pixel vector into an angle vector based on a conversion relationship between a diagonal angle of view of a current focal length range and a diagonal pixel of an image sensor of a camera system; and controlling the object to be close-up being moved to the center point of the screen based on the angle vector.

An intelligent control method and system using a radar security camera are disclosed, wherein a target is detected by 360° radar sensing regardless of the rotation radius of a camera by using the security camera having a built-in radar, and the camera is enabled to track the target according to the moving direction and specific signs of the target after the target is identified as a person and a vehicle sequentially according to a decision priority order.

An intelligent control method and system using a radar security camera are disclosed, wherein a target is detected by 360° radar sensing regardless of the rotation radius of a camera by using the security camera having a built-in radar, and the camera is enabled to track the target according to the moving direction and specific signs of the target after the target is identified as a person and a vehicle sequentially according to a decision priority order.

A method includes receiving selection of a target within an image captured by an image sensor of a payload and displayed on a user interface of the payload, detecting a deviation of the target from an expected target state within the image, generating, based at least partly on the deviation, a payload control signal including a first angular velocity for rotating the payload about an axis of the carrier to reduce the deviation about the axis in a subsequent image, and generating a base support control signal including a second angular velocity for rotating the payload with respect to the axis. When the first and second angular velocities are received, the carrier is controlled to rotate the payload at a third angular velocity about the axis. The third angular velocity is the first angular velocity, the second angular velocity, or a combination of both.

An object or body-mounted camera apparatus for recording surgery is provided that is adapted for tracking a relevant visual field of an on-going operation. To help maintain visibility and/or focus of the visual field, specific machine learning approaches are proposed in combination with control commands to shift a physical positioning or a perspective of the camera apparatus. Additional variations are directed to tracking obstructions based on the visual field of the camera, which can be utilized for determining a primary recording for use when there are multiple cameras being used in concert.

A system, computer-implemented method and non-transitory computer readable medium storing instructions for generating a two-dimensional (2D) map of an area of interest are provided. The system comprises a processor and memory storing instructions which when executed by the processor configure the processor to perform the method. The method comprises determining a perimeter of an area of interest, obtaining nadir images of the area of interest, obtaining at least one oblique image of the area of interest from at least one corner of the perimeter, and processing the nadir and oblique images together to form the 2D map of the area of interest.