39 results about "Camera control" patented technology

This application provides an AI-based camera control method, device, and storage medium, relating to the field of intelligent monitoring. It solves the technical problems of resource competition and conflict during multi-camera collaborative tracking, and low monitoring efficiency due to a single control strategy. The method includes: acquiring the current state information of at least two cameras within a target monitoring area, and the motion trajectory of at least one target object within the field of view of the at least two cameras; constructing a conflict detection model based on historical current state information and motion trajectories; identifying camera combinations with tracking competition within the target monitoring area as game participants based on the conflict detection model; constructing a multi-objective optimization-based payoff factor for the game participants; determining the optimal control strategy combination based on the payoff factor, and sending control operation commands. This application can improve the overall efficiency and intelligence level of the monitoring system.

This invention provides an electronic device, a control method, and a program for controlling its operation using arbitrary expressions in automated operations based on user instructions. [Solution] In the text generation AI service, the smartphone app receives a camera control voice instruction M111 from the user 101, interprets the received voice instruction, converts it into text data, and sends a camera setting item list request message M112 to the camera 102. The camera responds to the camera setting item list request message. When the smartphone app receives the camera setting item list request response M113 from the camera, it creates a camera setting item selection prompt M114 and sends it to the text generation AI service 104. The text generation AI service responds with a selection result M115 indicating which setting items should be changed in order to take a photo that meets the photographer's requirements.

The invention provides a control method and system based on a central control display screen and a camera of an intelligent automobile, and the method comprises the following steps: obtaining an original video stream of an in-automobile scene through an in-automobile camera module, and carrying out the preprocessing of the original video stream of the in-automobile scene through an RGB-IR ISP on the central control display screen, and obtaining an enhanced image; processing the enhanced image through a visual algorithm to obtain a perception result; reducing the LVDS signal of the sensing result into an RGB signal through a deserializer to obtain a final image; and adjusting parameters of the in-vehicle camera module according to the in-vehicle ambient light, the brightness component of the final image and a preset decision. According to the control method for the central control display screen and the camera based on the intelligent automobile, centralized cooperative control is achieved through a single MCU, and a plurality of intelligent closed-loop systems are formed.

Systems, apparatus, and methods of rendering content based on a control point of a camera device are disclosed. In an example, a marker is attached to the camera device and its pose is tracked over time. Based on a camera model of the camera device, an offset between the marker and the control point is determined. The tracked pose of the marker can be translated and / or rotated according to the offset to estimate a pose of the control point. The rendering of the content is adjusted over time based on the estimated poses of the control point. Upon presentation of the content in a real-world space (e.g., on a display assembly located therein), the camera device can capture the content along with other objects of the real-world space and generate a video stream thereof.

A method and apparatus for camera control to acquire images. The method includes: acquiring an image frame stream comprising at least one frame by an image sensor; acquiring a target frame by the image sensor; determining scene information in the target frame; selecting a reference frame from the image frame stream by identifying the scene information of the target frame in the reference frame; determining at least one acquisition parameter of the reference frame; and acquiring a final image from the target frame using the acquisition parameter.

This camera control program causes a computer to execute a process of controlling driving of a camera by instructing the camera to operate at a panning speed determined according to a moving speed of a subject in a panning direction, if the moving speed of the subject in the panning direction is equal to or greater than a predetermined value.

This invention discloses a fruit-picking and collecting device, including a bracket fixed to a vehicle body and an adjustable guide assembly mounted on the bracket. The guide assembly includes a first telescopic cylinder connected to the bracket and a second telescopic cylinder hinged to the output end of the first telescopic cylinder. A picking mechanism is connected to one side of the output end of the second telescopic cylinder, and a collecting mechanism is connected to the other side. A camera connected to a controller is mounted on the picking mechanism. In use, the camera controls the picking mechanism to pick fruit, which falls directly into the collecting mechanism. This invention features a vehicle body for moving the guide assembly, the picking mechanism, and the collecting mechanism. The camera connected to the controller allows for observation and real-time adjustment of the picking angle of the picking mechanism. Furthermore, the picking mechanism can pull branches and move individual fruits to the feeding end of the collecting mechanism, improving the accuracy of the picked fruit falling into the collecting mechanism.

The present disclosure provides a camera control method, comprising: obtaining shooting data of a camera; determining a use scenario of the camera based on the shooting data; in response to determining that the camera is currently in a target use scenario, configuring the camera to enter a focus lock state, different target focus parameters being fixed in different target use scenarios; and in response to determining that the camera is in a non-target use scenario, configuring the camera to be in an autofocus mode.

The present application relates to the technical field of artificial intelligence and computer vision, in particular to a digital person video generation method with camera control. The method comprises the following steps: S1: injecting camera control into model architecture design to generate a deep architecture from physical parameters to feature injection, the deep architecture comprising a Plücker camera encoder, a camera control injection mechanism based on a diffusion transformer, and a post adapter module; S2: setting a hybrid fine-tuning strategy, using a pre-trained digital person video generation model as a base model, and adopting a full-parameter training and LoRA fine-tuning hybrid training strategy; S3: setting a time step-aware dynamic window range strategy, and adopting a double-layer circulation mechanism to support the generation of long videos with a generation time longer than the limit of a single inference window. The present application can generate a person speaking video with specific camera operation effects according to a reference image, driving audio, a text prompt, and a camera trajectory file.

This invention discloses a traffic indication method, apparatus, system, and storage medium. The method is applied to a traffic indication system, which includes a camera and a projection module mounted on the camera. The projection module includes 2N lenses, a projection light source, and a holographic projection device, where N is an integer greater than or equal to 1. The method includes: in response to a traffic indication event being triggered, the camera controls the projection light source to image traffic indication information through the 2N lenses onto the holographic projection device; the holographic projection device holographically projects the real image of the traffic indication information onto a preset location area; wherein the preset location area includes the vehicle's windshield and a preset ground area. This solution can effectively ensure the effectiveness and visibility of traffic indication information for the driver, thereby effectively improving the driver's driving experience and safety.

The application relates to the technical field of bridge inspection, and discloses a bridge intelligent inspection camera control and image processing method, which comprises the following steps: acquiring bridge data and constructing a bridge BIM model; determining the coordinate mapping relationship between a virtual viewpoint and a camera, comparing the visual angle deviation of the virtual viewpoint and the camera, and determining a visual angle deviation compensation value; dividing an inspection area for each camera; judging whether an inspection task is triggered according to meteorological condition data and traffic flow data; when it is judged that the inspection task is triggered, controlling the camera to collect images based on the inspection area and the visual angle deviation compensation value; and cutting key areas of the collected images based on an edge server, generating standard images, and uploading the standard images to a cloud server for disease identification. The application improves the inspection positioning accuracy and the automation level.

This invention relates to the field of automatic control technology, specifically to a control method and system for a wide-temperature adaptive continuous zoom television camera. The method includes: acquiring the zoom-focus mapping relationship, inherent integrated time delay, mechanical inertia time delay, depth of focus, and absolute position data of the zoom motor of the continuous zoom television camera; calculating transient motion parameters; determining the dynamic lead displacement based on the inherent integrated time delay; deriving the reference and predicted focus positions from the mapping relationship; determining the defocus vulnerability based on the depth of focus; extracting the zoom-focus sensitivity; determining the focus displacement compensation amount based on the transient motion parameters and mechanical inertia time delay; and using the defocus vulnerability to weight and correct the focus displacement compensation amount and superimpose it onto the predicted focus position to generate adaptive feedforward focus target coordinates. This method improves the focus following accuracy in wide-temperature operating conditions and high-dynamic continuous zoom processes.

The application discloses a dual-camera holder camera control method and system, a dual-camera holder camera and a medium, and relates to the technical field of control. The method comprises the following steps: monitoring the screen support rotation parameter of the dual-camera holder camera, controlling the dual-camera holder camera to switch to the target screen mode corresponding to the screen support rotation parameter according to the screen support rotation parameter; determining the screen display strategy of the dual-camera holder camera according to the target screen mode, and controlling the dual-camera holder camera to perform screen display according to the screen display strategy; obtaining the user operation parameter of the dual-camera holder camera, and controlling the camera scheduling of the dual-camera holder camera according to the user operation parameter. In this way, the screen mode is intelligently switched by monitoring the screen support rotation parameter in real time, the preview black edge and UI blocking composition are avoided, the dual-camera is dynamically scheduled in combination with the user operation parameter, the naturalness of human-computer interaction and the shooting response efficiency are improved, the multi-angle viewfinder and shooting scene adaptation capability are significantly enhanced, and the user manual adjustment frequency is reduced.

The application discloses a kind of video inspection methods based on 2D visualization, comprising: calling inspection configuration library, parsing and displaying the configuration distribution diagram and inspection route in inspection configuration library;Select the video inspection of inspection route corresponding to configuration distribution diagram, and inspection route includes camera sequence list and camera control parameter;According to the real-time video of camera sequence list calling camera is played, and according to camera control parameter control camera video acquisition;When the real-time video of multiple cameras needs to be multicast, pop up several windows, and each window corresponds to play the real-time video of a camera.The application fully utilizes camera resources to play video inspection by the setting of camera sequence list and camera control parameter in inspection route, while intuitively displaying the position of camera, monitoring area and inspection route in configuration distribution diagram;And configuration distribution diagram and inspection route are stored in inspection configuration library corresponding to facilitate calling and modification.

The application discloses a kind of identification methods for high orbit space infrared camera control system, comprising: establishing the equivalent direct current motor model under ideal frictionless condition;Establishing speed position double closed loop control system;Determine the system balance working point;Design balance point sweep input signal;Get boundary sweep signal;Obtain angle output signal;According to angle output signal, the control object balance point nominal model g ture And boundary model g 边界 Is obtained by identification fitting;Design PID control rate C s , evaluation C s The reliability of high orbit space infrared camera control system in orbit control under nominal model and the robustness of high orbit space infrared camera control system in orbit control under boundary model.The application will be applied to space infrared camera spin-scan mechanism system model identification based on the coarse and fine combination of camera working balance point dynamic system model identification method, can improve the identification efficiency and accuracy of space spin-scan mechanism model, improve the stability and reliability of infrared camera overall control.

This invention discloses an AR inspection intelligent camera control and AI recognition method and related equipment, belonging to the interdisciplinary field of industrial intelligent inspection and augmented reality technology. The method includes: real-time monitoring of the light intensity in the current environment of the inspected equipment and the reflectivity of the target material of the inspected equipment; adaptively activating the corresponding acquisition module to acquire target image data of the inspected equipment; real-time recognition of the target image data through a lightweight AI model deployed on an edge computing device to obtain equipment status information and operation behavior information of the inspected equipment; compliance verification of the operation behavior information; if a violation is found, a warning message is output through the augmented reality interface, and the corresponding defect handling process is triggered. This invention can complete the inspection task in real time and efficiently, comprehensively improving the shortcomings of existing technologies such as low recognition accuracy, weak operation guidance, and poor environmental adaptability.

The embodiment of the application discloses a camera control method, which comprises the following steps: receiving interaction data sent by a wearable device, wherein the interaction data comprises motion data of the wearable device; and performing corresponding camera control operation based on the interaction data. The embodiment of the application also discloses a camera and a wearable device.

This disclosure provides a control method, apparatus, storage medium, electronic device, and vehicle for a camera device. The control method includes determining the vehicle's driving and parking state based on its state parameters; determining the camera device's operating mode based on the driving and parking state; and adjusting the camera device's operating parameters based on the operating mode. This disclosure, by employing a camera device with adjustable operating parameters, enables real-time switching between multiple operating modes, such as short-range surround view and long-range monocular view, in various scenarios including slow driving, normal driving, and parking, thereby achieving multi-functional adaptive perception of the external environment across all scenarios.

A system, such as a driver monitoring system (DMS) for a vehicle, includes a first infrared (IR) camera, a second IR camera, a sensor, and a controller. The first camera is configured to output a first IR light, such as to illuminate a driver of the vehicle with the first IR light for use of the first camera in monitoring the driver. The second camera is configured to output a second IR light, such as to illuminate the driver with a second IR light for use of the second camera in monitoring the driver. The sensor is configured to detect the first IR light being outputted by the first camera. The controller is configured to control the second camera to not output the second IR light while the sensor detects the first IR light being outputted by the first camera.

The application discloses a kind of coal mine coal cutter multi-gimbal camera detection tracking methods, it includes the following steps: step S1, acquisition coal cutter image data;Step S2, the coal cutter target detection is carried out to the coal cutter image data collected;Step S3, execute multi-gimbal camera cooperative tracking algorithm;Step S4, generate gimbal camera control instruction generation and execute.The application provides a kind of coal mine coal cutter multi-gimbal camera detection tracking method, solves the problems such as frequent target loss, tracking delay, data redundancy, low positioning accuracy in the existing monitoring method, realizes the cooperative linkage and accurate control of multi-gimbal camera, carries out real-time, continuous, high-precision tracking monitoring to coal mine underground coal cutter operation target, satisfies the underground safety monitoring needs of coal mine intelligent mining.

This application relates to a camera control method, a camera, and a storage medium. The method includes: acquiring a current frame image in real time using the camera, and determining a corresponding current brightness value based on the current frame image; determining the brightness range of the current brightness value, and selecting a calculation method corresponding to the brightness range of the current brightness value to calculate a target brightness value for the next frame image; calculating target exposure parameters for the next frame image based on the current brightness value, the target brightness value, and the exposure parameters of the current frame image; if the target exposure parameters of the next frame image are the same as the exposure parameters of the current frame image, controlling the camera to take a picture using the target exposure parameters of the next frame image. This application consumes few computing resources and has high efficiency in adjusting exposure parameters.

The application relates to a detection display processing system of an underwater portable mechanism, which comprises an fisheye image detection module, which is used for cooperating with a camera control module to provide an fisheye image detection function; the fisheye image detection function specifically comprises the following steps: acquiring multiple underwater images in real time, and performing edge detection on the underwater images to obtain edge images; performing straight line detection on the edge images to obtain a straight line segment set; taking the geometric center of the edge images as an origin, dividing the image plane into multiple concentric ring regions, and calculating the bending degree of the straight line segments located in the concentric ring regions; judging whether each underwater image is an fisheye image according to the bending degree; and an fisheye image conversion module, which is used for cooperating with the fisheye image detection module to realize fisheye image conversion and obtain multiple normal view angle images. Compared with the prior art, the application has the advantages of high image recognition and conversion precision.

This disclosure relates to a camera control method, apparatus, electronic device, storage medium, and product. The method includes: when displaying an application interface of a first application, and the application interface has a viewfinder window, acquiring the time interval between two adjacent frames displayed in the viewfinder window, wherein the two adjacent frames are obtained based on image acquisition of the viewfinder area by a camera invoked by the first application; and when the time interval exceeds a duration threshold, increasing the camera's frame rate to shorten the time interval. This method can promptly detect and alleviate image display stuttering.

The application discloses a kind of soft material multi-mechanical parameter measuring device and method, belong to material parameter test technical field.The device includes the loading platform of placing material, for being punctured to soft material puncture component, for detecting the camera of soft material and puncture component contact surface topography, controller and include the data processor of processing soft material puncture force-displacement data, force-displacement data and the crack size of camera shooting are introduced into data processor, data processor extracts the characteristic value of each stage in force-displacement curve, after curve feature and crack size value are input into the multi-fidelity neural network in data processor pre-trained by experimental data and finite element data, obtain the multiple mechanical parameters of the soft material to be measured.The whole test device structure is simple, experimental cost is low, experimental processing is simple, and it is easy to promote, and has the advantage that only through single puncture experimental data obtains the multiple mechanical parameters of the soft material to be measured.

This invention provides an inspection dimming device that enables dimming control of the light source and camera shooting control in various combinations of light sources and cameras. [Solution] When a trigger signal St is input to this inspection dimming device 1, for each of the light source control terminals 131, ..., dimming control output is performed from the light source control terminals 131, ..., based on the light source setting values ​​for lighting ON / OFF, lighting time, and lighting brightness for each of the multiple reference periods stored in the light source setting value storage unit 1aa, and also based on the light source setting value for lighting delay time. For each of the camera control terminals 141, ..., shooting control output is performed from the camera control terminal 141, ..., based on the camera setting values ​​for shooting ON / OFF and shooting time for each of the multiple reference periods stored in the camera setting value storage unit 1ab, and also based on the camera setting value for shooting delay time.

This application discloses an AOV camera control method, device, electronic device, and storage medium, including: collecting target behavior feature data, environmental perception data, and time information corresponding to each data; dividing multiple preset behavior scenarios according to the feature dimensions of the target behavior feature data, and constructing a scenario time period association model in combination with the time information; extracting high-demand usage periods of the AOV camera based on the scenario time period association model, obtaining demand response data of the high-demand usage periods within a preset evaluation period, and determining the demand level of the high-demand usage periods based on the demand response data; obtaining the current battery level and real-time environmental perception data of the AOV camera, and controlling the working state of the AOV camera according to the demand level, the current battery level, and a preset environmental threshold.

This application relates to a camera control method, apparatus, system, electronic device, and storage medium. The method includes: acquiring an initial detection result of the camera's intelligent functions; if the initial detection result indicates that the camera's operating state is abnormal, controlling the camera to enter a first recovery mode, performing a reset operation on the camera's application software in the first recovery mode, and after resetting the application software, re-detecting the camera's intelligent functions to obtain a second detection result; if the second detection result indicates that the camera's operating state remains abnormal, controlling the camera to enter a second recovery mode, and performing a reset operation on the camera in the second recovery mode. This application solves the problem of low camera control efficiency and achieves a highly efficient and accurate camera control method.