406 results about "Camera control" patented technology

The invention discloses a system for improving the applicability of an intelligent camera, and relates to the technical field of intelligent camera shooting. RGB, infrared and depth sensors are used for cooperative sensing, a dynamic inter-frame interpolation algorithm is used for complementing video data, target trajectory prediction is carried out based on a target motion vector analysis algorithm in combination with a recurrent neural network LSTM + Kalman filtering, and the applicability of the intelligent camera is improved. Meanwhile, three-dimensional scene modeling and shielding recovery are introduced, and environment information complementation of a dead angle area is optimized; through a cross-camera target identity re-identification ReID algorithm, seamless tracking is carried out among multiple cameras by utilizing appearance characteristics, gait characteristics and biological characteristics of a target, and meanwhile, PTZ camera control is optimized in combination with reinforcement learning, and the angles of the cameras are dynamically adjusted; a generative adversarial network GAN based on space-time consistency is adopted, historical video data and environment modeling are combined, missing pictures in visual dead angles are intelligently complemented, and the continuity and authenticity of monitoring pictures are improved.

The invention relates to a cutting path generation system based on visual positioning, cutting equipment and a cutting method. The system comprises a scanning camera control module, an image acquisition and recognition module, an image processing module, a cutting path planning module and a cutting control module. According to the system, by combining a Laplace algorithm and an LBP and GLCM texture extraction technology, the boundary recognition problem under the condition that a pattern and a background are in the same color or low contrast is solved; the path smoothness and the cutting quality are improved by adopting contour optimization and curvature compensation algorithms, the cutting sequence is optimized by combining weighting functions of the area, complexity and overlapping degree, and material deformation is reduced. And motor driving is dynamically adjusted through PID control, and stable control over the speed of the tool bit is achieved. The method has the advantages of being high in recognition precision, high in adaptability, intelligent in path planning and stable in cutting process, the automatic cutting efficiency and the finished product quality of complex patterns or same-color materials are remarkably improved, and the overall cutting precision fluctuation is controlled within + / -2%.

The invention relates to the technical field of camera control, and discloses a megapixel camera control method based on multifunctional fusion. The method comprises the following steps: acquiring original image data of an image sensor, and preprocessing to generate an initial brightness distribution diagram; and calculating a scene dynamic range to determine a target exposure parameter set containing exposure time, a gain coefficient and an aperture value, synchronously analyzing color temperature information, matching a preset white balance model to output a correction coefficient, and combining the two to generate a first control instruction to be sent to the image sensor. Receiving a touch screen focusing signal, and extracting a focus area coordinate to adjust a stroke parameter of a focusing motor; ambient light intensity is monitored in real time, and when the ambient light intensity is lower than a preset threshold, a flash lamp compensation module is activated and a compensation light quantity value is calculated. In the photographing mode, the output power of the flash lamp is adjusted according to the compensation light quantity value, the target exposure parameter set is recalibrated based on the focus area coordinates, and the camera complex scene adaptation and imaging quality are improved.

It is possible to generate an image captured with a camera control parameter optimum for a clipped image of a partial region of a captured image by a camera, and to distribute, display, or record the image. The image processing device includes: a clipping execution unit that generates a clipped image obtained by clipping a partial region from a captured image by a camera; a camera control parameter determination unit that determines a camera control parameter optimum for the cut-out image; and a camera control unit that causes the camera to execute image capturing to which the camera control parameter determined by the camera control parameter determination unit is applied. The camera control parameter determination unit determines a camera control parameter of at least one of focus, exposure, white balance (WB), shutter speed, or aperture optimum for the clipped image.

A method for forming a processed video stream, comprising: capturing a first part of an input video stream using a camera and transmitting the first part of the video stream to a processing facility remote from the camera. At the processing facility, designating a first sub-region of the first part of the video stream for further processing. In dependence on the designation of a first sub-region. A first cropped video stream is formed by cropping the first part of the video stream to that sub-region. A processed video stream is formed incorporating the first cropped video stream.

The invention relates to the technical field of camera control, and discloses an outdoor monitoring camera control method and device based on solar panel power supply, and the method comprises the steps: inputting original image data collected by a monitoring camera into a Light-EMA module for feature enhancement and Haar wavelet downsampling processing, obtaining a target feature matrix, and obtaining a target feature matrix; the optimal parameters of the holder control are calculated; collecting solar voltage and current values and environment illumination intensity, and performing SOC calculation and LSTM-GRU neural network prediction to obtain an energy availability index; performing multi-objective optimization solution through a DSAC-CAL algorithm to obtain an optimal decision vector of a system action space; according to the optimal decision vector, the camera frame rate, the processor frequency, the wireless transmission power and the sleep period are regulated and controlled, a multi-module cooperative control signal is obtained, the position prediction precision is improved, the system energy consumption is effectively reduced, the working time of the solar camera is prolonged, and the all-weather operation reliability is improved.

The invention provides an intelligent camera scheduling algorithm and system based on unmanned aerial vehicle trajectory prediction, and relates to the technical field of unmanned aerial vehicle monitoring, and the algorithm comprises the steps: generating a prediction trajectory set containing space-time probability distribution based on the collected real-time flight data of an unmanned aerial vehicle in combination with a motion probability coupling model; according to the collected camera parameters and environment modeling data, generating a dynamic coverage model in combination with the prediction trajectory set; dynamically generating a target tracking priority weight based on the space-time probability distribution of the prediction trajectory set and the space coincidence degree of a preset geo-fencing region in the environment modeling data; based on the spatial constraint of the dynamic coverage model and the target tracking priority weight, generating an optimal camera scheduling scheme through a multi-target optimization method; and converting the optimal camera scheduling scheme into a camera control instruction, and performing closed-loop control based on the real-time deviation of the dynamic coverage model, thereby realizing intelligent cooperative scheduling and target tracking of the unmanned aerial vehicle monitoring system.

Systems and methods are disclosed related to a 3D grounded video foundation model. A video generation method and system provide 3D conditioning information to a video diffusion model to improve generated video quality (object and temporal consistency) that is grounded in three dimensions (3D). The video generation method and system also enable precise camera control, cinematic effects, and scene editing. Video output corresponding to a set of camera specifications is generated for a scene from input image(s) including one or more images of a static scene or a sequence of images (video) for a dynamic scene. The input image(s) are used to calculate a 3D cache representing the scene. The 3D cache is rendered according to the set of camera specifications to produce a frame sequence and a mask sequence that identifies missing pixels in each frame. The frame sequence is encoded and masked to generate the output video.

The invention relates to the technical field of unmanned aerial vehicle load system image registration, in particular to a visible light and infrared image registration fusion method for an unmanned aerial vehicle photoelectric turret. Comprising the following steps: measuring and calibrating a relationship between a visible light camera focal length and a visible light Y-direction field angle on the ground, recording the relationship between the field angle and the focal length as a file, and storing the file on a camera control panel; the camera control panel controls the movement of the visible light camera through a PID algorithm until the field angle of a single pixel of the visible light image is matched with the field angle of a single pixel of the infrared image; extracting different-source image descriptors, matching the different-source image descriptors, storing the projection relation of each pixel coordinate as a matrix A, and calling to complete registration; and calculating the local contrast and information entropy of the visible light image and the infrared image, dynamically adjusting the fusion proportion, and generating a registration fusion image. The method has the advantages that simple calibration on the ground is only needed; and after zooming, a registration algorithm is operated on an airborne computer, and the efficiency and accuracy of feature matching are improved in combination with a multi-scale descriptor.

A method for generating photorealistic 4D scenes from text inputs is disclosed. The method utilizes a text-to-video diffusion model to generate a reference video and a freeze-time video. A canonical 3D representation is reconstructed using deformable 3D Gaussian Splats (D-3DGS) based on the freeze-time video. Temporal deformations are learned to capture dynamic interactions in the reference video. The method employs a novel Score Distillation Sampling strategy combining multi-view and temporal aspects to enhance consistency and robustness. The resulting 4D scenes feature multiple objects interacting with detailed background environments, viewable from different angles and times. The method enables flexible camera control and integration with augmented and virtual reality applications. Some examples include features such as image-to-4D generation.

A refuse vehicle includes a chassis, a body coupled to the chassis and defining a refuse compartment, a lift assembly configured to lift a refuse container to dump contents thereof into the refuse compartment, a display interface, a plurality of cameras positioned to capture a plurality of different views from the refuse vehicle, and a controller. The controller is configured to assign priority values to the plurality of different views, compare the priority values, and display, on the display interface, at least one of the plurality of different views based on the comparison of the priority values.

The invention provides a data processing method and device of a camera control system, a vehicle and a storage medium. The method comprises the following steps: in response to the fact that an automatic driving domain controller is identified to be powered on, performing state detection on a cabin domain controller to obtain a first state detection result; in response to the first state detection result, determining that the cockpit domain controller is a current master control domain controller, and sending permission switching request information to the cockpit domain controller; permission switching response information corresponding to the permission switching request information is received; switching the current master control domain controller from the cockpit domain controller to an automatic driving domain controller in response to determining that the permission switching request information meets a preset switching condition based on the permission switching response information; and receiving environment image data of the camera module by using the automatic driving domain controller. According to the invention, the technical problems of high energy consumption and low response speed during data processing of a camera control system in the prior art are solved.

The invention discloses an image exposure parameter obtaining method and device, equipment and a medium, and relates to the field of image processing, and the method comprises the steps: a processor determines a current timestamp when obtaining a frame synchronization signal sent by a deserializer; obtaining a current frame exposure image sent by an image sensor in the camera, and determining image exposure starting time corresponding to the current frame exposure image based on the current timestamp and a preset time delay; wherein the current frame exposure image is an image obtained after a serializer in the camera controls an image sensor to start exposure based on a frame synchronization signal sent by a deserializer; the deserializer sends a frame synchronization signal to the serializer and the processor at the same time; the preset time delay is a difference value between the time when the serializer obtains the frame synchronization signal and the time when the image sensor starts to expose. Under the condition of not depending on the timestamp generation function of the image sensor, the image exposure starting time is calculated through the processor, the application range of the scheme is expanded, and the accuracy and the stability are higher.

The invention relates to the technical field of camera control, and discloses a camera control method and system based on multi-sensor data fusion. The method comprises the following steps: collecting a multi-sensor synchronous data set, and inputting the multi-sensor synchronous data set into a deep Q network for sensor performance evaluation to obtain a performance score set; environment adaptive weight distribution is carried out based on the performance score set, and confidence coefficient weight parameters and fusion detection threshold parameters of all the sensors are obtained; performing abnormal sensor identification on the multi-sensor synchronous data set to obtain a normal working sensor identifier and an abnormal sensor isolation instruction; the multi-sensor synchronous data set is subjected to weighted fusion, target detection confidence data is obtained, a camera parameter adjusting instruction of the RGB camera is generated according to the target detection confidence data, the technical defect that a traditional method is poor in adaptability in a complex environment is overcome, and intelligent self-adaptive adjustment of the focal length, exposure and the pan-tilt angle is achieved.

The invention provides a steel surface defect detection and identification system and method based on a deep learning YOLOv8 model, and the system comprises an industrial camera which is disposed in a to-be-detected region of a steel production line and is provided with a high-brightness light source. The system is characterized by further comprising an image acquisition module, a fault detection module, a defect identification module and a man-machine interaction module which run on a computer and are connected with the industrial camera control system, and the method comprises the following steps: S1, system initialization, S2, image acquisition, S3, image preprocessing, S4, feature extraction and fusion, S5, defect identification and classification, and S6, result output and interaction. Automatic and precise steel surface defect detection and recognition of the whole process from image acquisition, defect detection to result output are achieved, manual visual judgment is not needed, detection standards are unified, the problem of unstable detection caused by manual experience differences is avoided, the labor intensity of operators is reduced, enterprise losses caused by defective steel circulation are avoided, and the production efficiency is improved. Reliable data support is provided for production process optimization, and the steel quality is guaranteed.

The invention relates to the technical field of unmanned aerial vehicle load system image registration, in particular to an infrared image and SAR image registration fusion method in dynamic flight of an unmanned aerial vehicle. Comprising the following steps: measuring and calibrating a relationship between an infrared camera focal length and an infrared Y-direction field angle on the ground, recording the relationship between the field angle and the focal length as a file, and storing the file on a camera control panel; the camera control panel controls the movement of the infrared camera through a PID algorithm until the field angle of the single pixel of the infrared image is matched with the field angle of the single pixel of the SAR image; extracting different-source image descriptors, matching the different-source image descriptors, storing the projection relation of each pixel coordinate as a matrix C, and calling to complete registration; and calculating the local contrast and information entropy of the infrared image and the SAR image, dynamically adjusting the fusion proportion, and generating a registration fusion image. The method has the advantages that simple calibration on the ground is only needed; and after zooming, a registration algorithm is operated on an airborne computer, and the efficiency and accuracy of feature matching are improved in combination with a multi-scale descriptor.

The invention relates to the technical field of multi-modal data processing, and discloses a camera control method and device based on multi-modal scene recognition, and the method comprises the steps: obtaining a multi-modal data stream containing vision, environment and vibration sensor delay data, and integrating and calculating a current scene modal distribution result; according to the monitoring data flow speed, identifying an abnormal scene to obtain an abnormal identification result; analyzing data real-time requirements, improving priority features, adjusting acquisition parameters, and forming an adjusted acquisition strategy; optimizing a transmission queue based on a strategy, extracting buffer data and simplifying the buffer data; generating a control instruction according to the simplified data, and issuing the control instruction to obtain a real-time feedback loop result; data streams are collected again and sorted for the second time, and an optimized multi-modal fusion sequence is obtained through integration; calculating an abnormal risk level, and combining with the simplified data to obtain an abnormal recognition enhancement result; and a final control instruction is generated and issued, and final decision data is fed back and generated. According to the method, scene changes can be dynamically adapted, and the anomaly recognition accuracy and the camera control timeliness are improved.

The invention discloses a high-speed camera for semiconductor graph-free dark field detection and a detection method, and relates to the technical field of semiconductor detection, and the method comprises the steps: integrating an adjustable laser light source array, a high-performance TDI camera and a pre-scanning sensor, carrying out the brightness information collection of a pre-scanning region, and generating a pre-scanning reflectivity graph; sequentially irradiating a pre-scanning area with different illumination light through an adjustable laser light source array, generating a plurality of scanning images, and extracting features to generate a multi-modal differential feature field; predicting a main defect type in the region through a multi-mode illumination and defect feature collaborative enhancement algorithm to generate a corresponding illumination mode instruction; calculating an optimal TDI parameter through a TDI parameter dynamic modulation algorithm to generate a TDI camera control instruction; and scanning the wafer according to the two instructions, collecting original image data, inputting the original image data into the depth defect classification model, and outputting a defect information graph and corresponding information. The invention aims to solve the problem that semiconductor detection precision and efficiency are difficult to balance.

The invention relates to a camera point location offset detection and automatic calibration method suitable for high-voltage equipment monitoring. The method comprises the following steps: constructing current preset bit reference primitive information; constructing a mapping relation between a unit PT step length and an imaging space in the current scene; constructing a multi-layer surrounding type auxiliary reference primitive information matrix; judging whether the camera deviates or not; searching optimal matching meta-information; and calculating a deviation rectification PT value, and carrying out PTZ camera control and deviation rectification. According to the method, high-precision automatic correction of the preset position of the camera in high-voltage equipment monitoring is realized, key feature points of power equipment can be stably extracted in a complex field environment by fusing local feature matching and a dynamic key point selection mechanism, and the matching accuracy is greatly improved; actual deployment shows that the repeated positioning precision of the preset position can be improved to + / -2 pixels from original + / -15 pixels, the manual rechecking frequency is remarkably reduced, and differential requirements of equipment of different voltage grades on the inspection precision are met.

The invention provides a camera control method and related equipment thereof, and the method comprises the steps: detecting an observation region through a radar, and judging whether a target person exists in the observation region or not; if yes, radar point cloud information in the observation area is acquired, and position information of the target person is determined; according to the position information, designated feature information of the target person is obtained, the motion state of the target person is recognized, and the designated feature information comprises at least one of Doppler velocity information, micro-Doppler frequency information and position information; and activating a camera according to the motion state of the target person, and outputting position information of the target person. Through fusion of the radar and the camera, the radar serves as an activation switch for working of the camera, so that the camera is started to work when needed, and the power consumption of the camera is reduced. In addition, the information of the target position can be acquired in real time through the radar, and the target person can be accurately positioned.

The invention discloses a camera shooting control method and device using an optical fiber signal, equipment and a medium. After the system is powered on, the upper computer sends control commands such as communication and triggering, the control commands are converted into optical signals through the electro-optical conversion module, the optical signals are sent to controlled equipment (including a camera unit, a light source unit and an aperture unit) through optical fibers (plastic optical fibers and silica optical fibers), the optical signals are converted into electric signals through the photoelectric conversion module, and the system works based on the control commands. Operation such as camera exposure, light source flashing and aperture opening and closing is achieved, and ideal control states of good image sensitization, light source synchronization and moderate aperture are achieved. Compared with a traditional control mode that electric signals are transmitted through cable media, optical signals are transmitted through the optical fiber media, the electromagnetic interference influence can be reduced, the transmission distance is longer, the cable weight is lighter, the error control probability is reduced, and the overall system robustness is effectively improved.

The invention discloses a camera control method and device, electronic equipment and a storage medium, and the method comprises the steps: controlling a first camera to monitor a target region, recognizing an abnormal event, receiving an abnormal event sensing signal fed back by the first camera and corresponding abnormal event video data, responding to the abnormal event sensing signal, and outputting the abnormal event video data. And awakening the second camera, controlling the awakened second camera to dynamically collect video data of the target area, analyzing the video data of the target area and the abnormal event video data, generating an abnormal event analysis result and an abnormal event processing completion signal, and controlling the second camera to enter a dormant state according to the abnormal event processing completion signal. According to the invention, automatic image acquisition and recognition can be realized, power consumption is reduced, the method is suitable for image acquisition scenes under various environmental conditions, the accuracy of image recognition is improved, and the method can be widely applied to the technical field of camera control.

The invention discloses an absolute scale camera track image-to-video generation method suitable for a real scene. The method mainly comprises the following steps: reconstructing a relative scale 3D point cloud by using a multi-view reconstruction method; reconstructing an absolute-scale 3D point cloud by using a monocular depth prediction method; calculating a scene scale zoom factor from the relative scale to the absolute scale, and aligning the relative scale camera pose to the absolute scale camera pose; the absolute scale camera track is injected into the diffusion model, model training is carried out based on denoising loss, and a scene scale consistency diffusion model is obtained; in a high-noise stage, a scene constraint method without training is used for shaping a picture layout of a scene scale consistency diffusion model, the dynamic consistency is improved, and a real scene video is generated. According to the method, high-precision camera mirror movement and scene scale consistency training are supported, and the problems of inaccurate camera control, inconsistent scene scale and the like in the prior art are solved.

The invention discloses a video generation method and system based on a scene adaptive track and mirror moving control, and belongs to the technical field of computer vision. The method comprises the following steps: firstly, aligning a scene point cloud and a parameterized human motion sequence to a unified coordinate system, generating a ground adaptive three-dimensional track according to a two-dimensional track input by a user and scene geometry, and redirecting the motion; projecting the three-dimensional information into a two-dimensional condition graph based on camera parameters; and finally, in a conditional diffusion model generation process, selectively fusing scene geometric condition information after noise addition into the current denoising latent variable by utilizing a visibility mask generated by the depth map, so as to realize view angle self-adaptive mirror operation control. According to the method, the problems of conflict between character motion and scene, inflexible track control and inconsistent background under camera motion are solved, and a controllable video which is physically consistent and visually real can be generated.

An imaging system is provided that includes a video endoscope having a handle and an endoscope. The endoscope includes an image sensor fixedly mounted within the endoscope. The capacitive sensing unit is disposed along an outer surface of the handle. The capacitive sensing unit includes a plurality of capacitive sensors disposed on an outer surface of the handle. The handle includes an electronic controller operable to process actuation of the plurality of capacitive sensors in order to control the camera control function and determine the medical procedure and / or the identity of the user.

The invention relates to the technical field of image acquisition, in particular to an image acquisition device, an image acquisition method, electronic equipment and a storage medium. According to the embodiment of the invention, camera calibration parameters need to be acquired through the image acquisition calibration module, the trigger signals are generated in the multi-camera control module, and the trigger signals are respectively sent to the light field camera imaging module and the event camera imaging module; the light field camera imaging module and the event camera imaging module carry out data acquisition in the same detection time slot; in a light field camera imaging module, collecting light field data of a target scene in a detection time slot according to the trigger signal; in an event camera imaging module, event data of a target scene are collected in a detection time slot according to the trigger signal; and in the data fusion module, image acquisition fusion data is generated according to the camera calibration parameters, the light field data and the event data. Therefore, high-quality real-time imaging can be realized.

Systems and methods employing a surgical robotic surgeon console with a display for use by a surgeon in a remote surgery are provided. The surgical robotic surgeon console includes a console frame and a horizontal member connected to the console frame. the horizontal member extending outwardly from the console frame and positioned above the display. Also provided is a head bar mounted on the horizontal member and the head bar configured to support a user's head relative to the display. Also provided is a system for camera control based at least in part on live gaze location information.

To provide an imaging device used in an imaging system in which both the imaging device and an accessory device are capable of implementing FP functions, and which allows the initial setting of the FP functions to be appropriately performed.SOLUTION: An imaging device (200) to which at least one accessory device (100) can be detachably connected comprises: camera communication means (202) capable of communicating with the accessory device; and camera control means (201) that is capable of receiving first initial setting information regarding the initial setting of a first function which drives a focus lens to a predetermined first focus position from the accessory device, and that has a second function capable of requesting the accessory device to drive the focus lens to a predetermined second focus position. The camera control means sets second initial setting information about the initial setting of the second function such that it differs at least partially from the first initial setting information on the basis of the first initial setting information.SELECTED DRAWING: Figure 7

The invention relates to the technical field of photoelectric tweezers, in particular to a system for achieving operation of the photoelectric tweezers. According to the technical scheme, the system comprises a camera, an imaging barrel lens, a beam combiner, a projection system, a fluorescence module, an objective lens turntable, an electric XYZ platform, a signal generation system and a control module, the camera captures a microscopic objective lens imaging light beam through the imaging barrel lens, and the beam combiner is used for projecting a microscopic light beam and reflecting a projection light beam; the projection system is composed of an LED light source, an array reflector set and the like and projects controllable light spots under an objective lens. The fluorescent module switches a bright field mode and a fluorescent mode; the objective lens turntable automatically switches multiplying power; the electric XYZ platform is used for fixing and positioning a biological chip; the signal generation system outputs an electric signal of the control chip; the control module is divided into a camera control part, a projection part and a motor part to cooperatively complete photoelectric tweezer operation. The photoelectric tweezers operation and the fluorescence operation are completed by one system, and the photoelectric tweezers operation and the fluorescence operation are controlled through a proper control process.

A vehicular vision system includes an electronic control unit (ECU) configured, when installed in a vehicle, to connect via a plurality of coaxial cables of the vehicle with a plurality of vehicular cameras of the vehicle. Each camera is operable to capture image data. The coaxial cables (i) carry image data captured by the respective camera from the respective camera to the ECU, (ii) carries camera control data from the ECU to the respective camera and (iii) connects a DC power supply of the ECU to the respective camera for powering the respective camera. The camera control data is carried by the respective coaxial cable from the ECU to the respective camera at a control data carrier frequency that is lower than an image data carrier frequency at which image data captured by the respective camera is carried by the respective coaxial cable from the respective camera to the ECU.