A method of controlling an image acquisition device for tracking a target object includes: detecting an event in which tracking of a first object, which is a tracking target object, fails in a first image acquired by the image acquisition device; determining, in the first image, a reference object which is used as a reference for controlling the image acquisition device; controlling the image acquisition device such that at least one of an image capturing range and an image capturing direction of the image acquisition device is adjusted based on at least one of a size and a location of the reference object in the first image; and recognizing the first object in a second image acquired by the image acquisition device in a state in which at least one of the image capturing range and the image capturing direction is adjusted.

A system and a method for automatic video redaction are provided herein. The method may include: receiving, an input video comprising a sequence of frames captured by a camera, wherein the input video includes live video obtained directly from the camera, wherein recordation of the video directly from the camera is disabled; performing visual analysis of the input video, to detect portions of the frames of the input video in which one of a plurality of predefined objects or a descriptor thereof is detected; generating a redacted input video by replacing the portions of the frames with new portions of another visual content; and recording the redacted input video on a data storage device, wherein the generating of thethe redacted input video, is carried out by a computer processor, after the input video is captured by the camera and before the recording of the redacted input video on the data storage device.

An imaging system including an imaging device 501 and a recording server 502 communicatively connected to the imaging device 501, wherein the imaging device 501 includes an imaging unit 503 that generates a video with a plurality of resolution, a dividing unit 504 that performs a division process of dividing the video generated by the imaging unit 503 into one or a plurality of tile areas and generates a tile image, and a transmission unit 506 that transmits the video to the recording server 502, wherein the recording server 502 includes a division control unit 507 that outputs an instruction to change a division method for the division process to the imaging device according to a designation frequency of an area designated on the video transmitted from the imaging device 501.

An imaging system including an imaging device 501 and a recording server 502 communicatively connected to the imaging device 501, wherein the imaging device 501 includes an imaging unit 503 that generates a video with a plurality of resolution, a dividing unit 504 that performs a division process of dividing the video generated by the imaging unit 503 into one or a plurality of tile areas and generates a tile image, and a transmission unit 506 that transmits the video to the recording server 502, wherein the recording server 502 includes a division control unit 507 that outputs an instruction to change a division method for the division process to the imaging device according to a designation frequency of an area designated on the video transmitted from the imaging device 501.

A camera system includes an administrator and a series of camera nodes which includes an audio microphone for also including sound in the video data file. The administrator includes a computer server, a wireless transmitter/receiver (transceiver), and machine learning (ML) chips. Each camera node includes a video capturing device or camera, a wireless transmitter/receiver (transceiver), a plurality of ML chips, and a GPS sensor. The ML chips are capable of receiving data in the form of a video file and processing the data to determine if the data includes “actionable” data. The ML chip makes certain inferences from the captured video data. The camera nodes are wirelessly linkable to each other. The communication between the several camera nodes form a “mesh network” wherein the several camera nodes may transmit data to each other, thus propagating the camera nodes with the mesh network with common data, rules, or inferences.

Methods, systems, and apparatus for camera detection of human activity with co-occurrence are disclosed. A method includes detecting a person in an image captured by a camera; in response to detecting the person in the image, determining optical flow in portions of a first set of images; determining that particular portions of the first set of images satisfy optical flow criteria; in response to determining that the particular portions of the first set of images satisfy optical flow criteria, classifying the particular portions of the first set of images as indicative of human activity; receiving a second set of images captured by the camera after the first set of images; and determining that the second set of images likely shows human activity based on analyzing portions of the second set of images that correspond to the particular portions of the first set of images classified as indicative of human activity.

Provided is a user equipment for controlling a drone. The user equipment analyzes an original video to control the drone to photograph a reproduction video giving a feeling identical to or similar to the original video. An electronic device may be connected to an artificial intelligence module, a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 5G service, and the like.

A disclosed spacecraft is provided with: an attitude control actuator configured to control an attitude of the spacecraft; an imaging device configured to receive an optical communication signal from another spacecraft; and an attitude controller configured to control the attitude control actuator, based on a position of the optical communication signal in an image obtained by the imaging device.

This disclosure describes systems and methods for a multipoint cable cam (MPCC) of an aerial vehicle. A method includes operations of receiving user input associated with a predetermined path and correlating the received user input with stored global positioning satellite (GPS) data to generate one or more virtual waypoints along the predetermined path. The method includes processing the one or more virtual waypoints to generate a spline-based flight path. The method may include storing the spline-based flight path and transmitting the spline-based flight path to the aerial vehicle.

A communication terminal includes a memory and circuitry. The memory stores, for each image type information indicating a type of image data, sizes of a plurality of display areas, each display area being a divided area divided from an entire area displayable by a display, in association with required resolutions of image data to be displayed in the corresponding display areas. The circuitry receives, from a communication management system, specific image type information indicating a type of specific image data transmitted from other communication terminal. The circuitry transmits, to the communication management system, specific required resolution, which is a resolution stored in the memory for the specific image type information in association with the size of one of the display areas in which the specific image data is to be displayed.