223 results about "Camera control" patented technology

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.

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.

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.

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 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 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.

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.

The invention belongs to the field of panoramic stitching digital image processing technologies and camera ISP technologies, and particularly relates to a chromatic aberration consistency control method based on front and rear end collaboration. The method comprises the following steps: 1, acquiring statistical information of multiple cameras; step 2, acquiring a current camera control parameter by adopting a front-end chromatic aberration consistency adjustment algorithm; 3, the current camera control parameters are issued to all the cameras, and all the cameras complete exposure imaging according to the current camera control parameters; step 4, acquiring an overlapped part image in each path of camera imaging; step 5, calculating a statistical histogram cumulative distribution function of overlapped part images in each path of camera imaging; step 6, calculating a histogram matching function according to the cumulative distribution function of the overlapped part images in each path of overlapped camera imaging, so that the histograms of the overlapped parts of the two images tend to be consistent; and step 7, according to the obtained histogram matching function, transforming the brightness channel of each pixel in the corresponding camera imaging to complete color difference consistency correction.

The utility model discloses a DSP camera control circuit of golf simulation system detector, 40 feet, 59 feet, 65 feet, 68 feet, 87 feet, 77 feet, 66 feet, 67 feet of blackfin digital signal processor U2 respectively correspond to be connected with resistance R2, resistance R3, resistance R4, resistance R5, resistance R6, resistance R7, resistance R8, resistance R9, 8 feet, 10 feet, 28 feet, 24 feet, 25 feet, 32 feet, 33 feet, 30 feet, 31 feet of CMOS image sensor U4 respectively correspond to be connected with resistance R12, resistance 13, resistance 14, resistance R15, resistance R16, resistance R17, resistance R10, resistance 11, resistance 19, the 23 feet of CMOS image sensor U4 is connected with CMOS logic chip U5, and the 5 feet of CMOS logic chip U5 connects electrolytic capacitor C2 and power supply end CAM3V3, and the resistance R18 is connected between the 1 foot and 3 feet of CMOS logic chip U5, and the 26 feet, 22 feet, 23 feet of CMOS image sensor U4 respectively correspond to be connected with resistance R20, resistance 21, resistance 22, and the resistance of the product plays current -limiting protection and impedance matching, and the protection circuit is prevented from being damaged.

Disclosed are a multi-camera control method, apparatus, and device, and a storage medium, relating to the field of intelligent driving. The method comprises: determining an interrupt pin state used to trigger an interrupt in a deserializer; in response to the interrupt pin state indicating that at least one camera among a plurality of cameras is in a disconnected state, determining port states corresponding to the cameras at a first moment; and in response to the port state corresponding to a first camera among the plurality of cameras at the first moment switching from a disconnected state to a connected state, restoring data output of the first camera. According to the technical solution of the present disclosure, the connection status of each camera is determined only when a hot-plug action occurs, and corresponding data output is restored when the camera switches from a disconnected state to a connected state, thereby saving processor resources. In addition, the port states corresponding to the plurality of cameras can be determined simply by means of one interrupt pin in the deserializer, thereby significantly reducing the consumption of hardware resources.

A camera controller for providing a camera control signal for commanding movement of a camera 1, comprises: an input device (e.g. joystick 6 or touch sensitive input) capable of sensing input position

Systems and methods for contextual camera controls during a collaboration session in a heterogenous computing platform are described. In an embodiment, an Information Handling System (IHS) may include: a heterogeneous computing platform comprising a plurality of devices and a memory coupled to the heterogeneous computing platform, where the memory comprises a plurality of sets of firmware instructions, where each set of firmware instructions, upon execution by a respective device, enables the respective device to provide a corresponding firmware service, and where at least one of the plurality of devices operates as an orchestrator configured to: determine a location of the IHS during a collaboration session, and in response to the determination, change a camera setting.

The utility model relates to a camera control circuit which comprises a first voltage transformation circuit, a second voltage transformation circuit, a main control circuit and a motor driving circuit. Wherein the first voltage transformation circuit is used for being connected with an external power supply so as to take electricity from the external power supply and output first working voltage, and the first working voltage is provided for the motor driving circuit; the second voltage transformation circuit is connected with the first voltage circuit and used for taking electricity from the first voltage circuit and outputting a second working voltage, and the second working voltage is provided for the main control circuit; the main control circuit is connected with the motor driving circuit, the motor driving circuit is at least used for controlling the camera to switch the shooting position, and the problems that in the prior art, a traditional camera control circuit is high in power consumption, low in response speed, insufficient in control precision and the like are solved.

1. The name of the design product: handheld gimbal camera control box. 2. The use of the design product: for connecting with handheld gimbal camera, charging handheld gimbal camera and realizing two-way data transmission. 3. The design points of the design product: in shape. 4. The picture or photo best indicating the design points: perspective view.

The invention provides a streaming media rearview mirror imaging control system, method and device and a storage medium. The system comprises a rearview camera, an intelligent driving domain control module, a main control module and a streaming media rearview mirror. The main control module is configured to issue a frame freezing instruction before the intelligent driving domain control module is started, issue an exposure mode switching instruction after the streaming media rearview mirror executes the frame freezing instruction, and issue a frame recovery instruction after the intelligent driving domain control module executes the exposure mode switching instruction; the streaming media rearview mirror is configured to continuously output a current frame of vehicle rear image as a cache frame after receiving a frame freezing instruction, and start to output the current frame of vehicle rear image in real time after receiving a frame recovery instruction; and the intelligent driving domain control module is configured to switch the rearview camera to external automatic exposure after receiving the exposure mode switching instruction. The problem that when the intelligent driving domain control module takes over the control right of the camera, the brightness of the image of the streaming media rearview mirror changes can be solved.

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.

The present application discloses an auxiliary lens-based gimbal camera system, comprising a gimbal, a camera provided on the gimbal, at least one auxiliary lens, and a main control assembly. The gimbal is used for adjusting the steering angle of the camera and / or the auxiliary lens. The main control assembly is connected to the gimbal, the camera, and the auxiliary lens, and is used for driving, on the basis of an external instruction, the gimbal to adjust the steering angle of the camera and / or the auxiliary lens, controlling the camera and the auxiliary lens to work so as to respectively capture a main picture and corresponding panoramic pictures, splicing and combining the panoramic pictures captured by the auxiliary lenses to obtain a spliced video stream, inputting, on the basis of the external instruction, the spliced video stream, the main picture, and the panoramic pictures into an algorithm model for processing, performing video mixing on the spliced video stream, the main picture, and the panoramic pictures to generate a corresponding video and outputting the corresponding video. Also disclosed is an auxiliary lens-based gimbal camera control method.

The invention relates to a camera control system and method for a computer-assisted surgical system. A camera control system may access surgical data for a surgical procedure, including performance of one or more operations performed by a computer-assisted surgical system. The camera control system may identify an event associated with the surgical procedure based on the surgical data, and may determine a location associated with the event based on the surgical data. In response to the determination of the location of the event, the camera control system may guide an automatic adjustment of the field of view of the camera to capture a particular field of view of the location associated with the event.

The invention discloses a five-axis galvanometer light beam five-dimensional integrated error correction system based on machine vision. The system comprises a vision measurement system, a Qt software system and a computer. The vision measurement system comprises a rotary table, an industrial camera and camera control software, and the rotary table controls the machining plane to rotate; the industrial camera communicates with the computer through the camera control software to shoot and store patterns; the Qt software system comprises a pattern processing module, an error measurement module and an error correction module; the computer runs a Qt software system on the basis of a Qt Creator framework, and the pattern processing module is used for controlling the five-axis galvanometer processing system to process patterns; the error measurement module measures light beam five-dimensional error data; and the error correction module fits an error function through the error data and feeds back the error function to a processing system for correction. According to the invention, pure machine vision five-dimensional error measurement is realized only by using the correction pattern on a single workpiece.

The invention discloses a camera steering adaptive control system based on sound source localization, and relates to the technical field of camera control, the camera steering adaptive control system comprises a cloud server, and the cloud server is in communication connection with the following modules: an end-side acoustic sensing module, which is used for collecting a sound signal through an acoustic array deployed on a camera terminal, and sending the sound signal to the camera terminal; the direction angle and the pitch angle of the target sound source are calculated by adopting a sound source positioning algorithm, and a preliminary PTZ control instruction is generated; based on sound source localization, the system can quickly lock the direction of a target sound source in a complex environment, the direction angle and the pitch angle of the target sound source are quickly calculated by using a sound source localization algorithm, a preliminary PTZ control instruction can be generated without cloud feedback, and a camera is driven to quickly turn to the approximate direction of the sound source. The response speed of the system to the sound source is greatly improved, and the camera is further finely adjusted by combining the accurate tracking instruction of the cloud comprehensive audio and visual information, so that the target tracking accuracy is ensured.

The invention relates to a parking space addressing method, a camera control method and device, computer equipment, a computer readable storage medium and a computer program product. The parking space addressing method comprises the following steps: performing numbering processing on each rod management group in a target parking area to obtain a group number corresponding to each rod management group; according to the position information of each multifunctional rod of each rod management group, determining a sorting sequence number corresponding to each multifunctional rod of each rod management group; for any multifunctional rod, according to the pixel coordinate of each parking space marking frame associated with any multifunctional rod, determining a sorting sequence number corresponding to each parking space associated with any multifunctional rod; and generating a parking space identifier corresponding to each parking space according to the sorting sequence number corresponding to each parking space in the target parking area, the sorting sequence number corresponding to each associated multifunctional rod and the group number to which the multifunctional rod belongs. By adopting the method, the intelligence of a parking space addressing mode can be improved.

The invention relates to a task-driven adaptive imaging method for power line anomaly detection, and the method comprises the steps: constructing a power line anomaly detection model, an adaptive camera control model and an image simulation model, and carrying out the combined optimization of the dynamic imaging parameters of a camera and a downstream anomaly detection task based on the three models. A dynamic mapping relation among ambient light, the moving speed of inspection equipment, dynamic imaging parameters and detection performance is established, and conversion from general imaging to task optimal imaging is realized. And the problem of poor performance of a downstream anomaly detection model caused by a general imaging means under complex illumination and motion in the existing routing inspection technology is solved. According to the invention, the image simulation model is utilized to obtain the data set for training the model based on the data set of the existing anomaly detection task, and the data set construction process is simplified.

The utility model discloses a camera control box circuit, a camera control box and shooting equipment, and the camera control box circuit comprises a first Type-C interface which is electrically connected with power supply equipment; the power supply output interface is electrically connected with the camera module; the input end of the first voltage reduction module is electrically connected with a VBUS pin of the first Type-C interface, and the output end of the first voltage reduction module is electrically connected with the power supply output interface; and the PD decoy module is electrically connected with the first Type-C interface so as to be in protocol communication with the power supply equipment. According to the technical scheme, the cost and the weight of the camera control box are reduced.

The invention provides a high-speed camera trigger control device and method, and is applied to the technical field of camera control. The equipment comprises a trigger threshold adjustment unit, a signal analysis and comparison unit and a camera trigger control and time service unit. The trigger threshold adjusting unit comprises an FPGA control chip and a DAC chip. The FPGA control chip responds to the threshold setting instruction to generate a threshold digital signal and generates a time frame in an ASCII format according to the IRIG-B time signal; the DAC chip generates a trigger threshold according to the threshold digital signal; the signal analysis and comparison unit generates TTL trigger signals when the target pulse signals meet a trigger threshold value, and the TTL trigger signals are used for triggering a plurality of high-speed cameras to carry out image acquisition; and the camera trigger control and time service unit adopts a coaxial cable to send TTL trigger signals to the plurality of high-speed cameras and adopts a twisted-pair cable to send time frames to the plurality of high-speed cameras. The method is suitable for synchronous trigger control and high-precision time synchronization of a plurality of high-speed cameras.

A camera controller for providing a camera control signal for commanding movement of a camera, the camera controller comprising: an input device, the input device being capable of sensing input position over a range of motion; and an electronic circuit for receiving sensed input position from the input device and forming the camera control signal, the circuit being arranged to form the camera control signal according to one of a plurality of control laws and to select independence on the sensed input position the control law to be used.

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.