28 results about "Visual projection" patented technology

The invention provides a multi-modal fusion and semantic enhancement train positioning method and system, and belongs to the technical field of rail transit, and the method comprises the steps: carrying out the time-space alignment of data, obtaining a dense point cloud, constructing a dense semantic point cloud, and dynamically estimating the confidence coefficient weight of each type of sensors; a set residual error and a Manhattan structure constraint residual error of a plane are constructed, laser radar point cloud parameters are obtained, and visual projection constraints are constructed at the same time; constructing a comprehensive degradation scoring function to carry out degradation judgment on the current environment; when the degradation result is yes, introducing a structure and motion information independent of an external environment, maintaining trajectory estimation, and constructing a compensation constraint; introducing a prior semantic constraint and a large model semantic factor constraint; and constructing a global optimization objective function, dynamically adjusting the weight of each modal factor, obtaining an optimal estimation state, and outputting a high-precision train positioning result. According to the method, high-precision and robust track estimation in an extreme scene is realized, so that the continuity, safety and intelligence of train positioning are guaranteed.

The embodiment of the invention provides a cluster collaborative navigation method, a control system and a storage medium. The method comprises but is not limited to the technical field of navigation. The method comprises the following steps: in an upper layer module of a gene regulation and control network, determining a form boundary curve according to first position information of first execution equipment, second position information of second execution equipment and third position information of an obstacle; in a lower layer module of the gene regulation and control network, determining a tangential propulsion speed component and an offset correction speed component according to the form boundary curve and the first position information; and in a lower layer module of the gene regulation and control network, according to a visual adjacent distance regulation speed component, a tangential propulsion speed component and an offset correction speed component of the visual projection field, determining a target linear speed and an angle parameter. According to the embodiment of the invention, collaborative navigation and dynamic form maintenance of the cluster system can be realized.

An electronic device, computer program product, and method provide autonomous projecting of a selected content to a second display. The device is configured to, in response to a trigger to transmit first content of the electronic device to a connected second electronic device for presenting on a second display: (i) determine whether second display content is currently being shared with at least one third electronic device; and (ii) in response to determining that the second display content is currently being shared with at least one third electronic device: (a) withhold automatic rendering of the first content on the second display; and (b) generate and output a notification presented on at least the first display, the notification informing a user of at least one of the electronic device and the second electronic device that the content presented on the second display is being shared.

The invention relates to the technical field of medical instruments and clinical nursing, in particular to a radial artery puncture navigation system based on multi-modal sensing and digital projection, which comprises the following steps: a multi-modal blood vessel signal acquisition module, which is used for acquiring a blood vessel pulsation signal on the wrist of a patient through a photoplethysmography sensor array, the strongest pulsation line is positioned through the pressure sensor array, and the blood vessel depth and artery and vein distinguishing information are obtained through the bioelectrical impedance sensor array. According to the invention, through multi-modal blood vessel signal acquisition, blood vessel dynamic deformation modeling, personalized digital twinning construction and dynamic updating, projection path generation and control, and projection output and real-time error compensation, real-time visual projection of a blood vessel center line and local deformation is realized; therefore, the problem that puncture positioning is not accurate due to the fact that dynamic changes of blood vessels cannot be accurately reflected due to the fact that most traditional radial artery puncture adopts a hand feeling positioning method is solved.

The invention discloses a movable road disaster night visual projection early warning method and device. The device comprises an electric carrying platform, a fixing device is arranged on the electric carrying platform, a telescopic device is arranged on the fixing device, a rotating device is arranged at the top end of the telescopic device, and a projection device is arranged on the rotating device; the telescopic device and the rotating device are combined for use, so that a projection picture is allowed to be accurately projected to a preset area, the projection accuracy is ensured, and the overall early warning efficiency of the early warning device is remarkably improved; the projection device enables an early warning sign and a signal to be clearly projected to the ground at night, so that a running vehicle can more strikingly receive early warning information, a driver is prompted to take prevention measures such as deceleration or parking, potential traffic accidents are effectively avoided, and the driving safety is improved. The technical problem that the early warning effect of an early warning device in the prior art is not obvious is solved.

The invention relates to the technical field of remote sensing vision, and particularly discloses a remote sensing multi-modal reasoning method and system based on a geospatial thinking chain, and the method comprises the steps: constructing a geospatial thinking chain data set which comprises structured reasoning data organized according to a planning-positioning-synthesizing three-section cognitive architecture, the association module is used for establishing verifiable association between visual evidence in a remote sensing image and a text conclusion; constructing a remote sensing visual language basic model, wherein the model comprises a visual encoder, a language decoder and a visual projection layer connecting the visual encoder and the language decoder; according to the method, remote sensing analysis is modeled into a verifiable multi-step reasoning process, so that the model provides a verifiable analysis track while outputting a final answer, the problem that output cannot be verified due to traditional end-to-end training is solved, the performance of a complex analysis task is remarkably improved, and meanwhile, the accuracy of the result is improved. And the conversion from opaque perception to structured and verifiable reasoning is realized.

The invention discloses a robot interaction intention projection method based on environmental perception, and belongs to the technical field of robot detection and human-computer interaction. The method comprises the following steps: S1, acquiring environment sensing data, robot state data and projection effect influence factors; s2, carrying out intelligent processing on the environment perception data, the robot state data and the projection effect influence factors, and generating an optimal projection decision; and S3, projecting a visual symbol according to the optimal projection decision, and automatically adjusting the projection effect based on the projection effect influence factors. According to the robot interaction intention projection method based on environmental perception, dynamic intention visual projection is generated by fusing the internal intention and the external environment information of the robot, and adaptive adjustment is performed on the visual projection image, so that efficient, safe and clear man-machine interaction is realized.

The invention provides a lip language recognition model construction method fusing external information, and the method comprises the steps: constructing an initial lip language recognition model which comprises a visual modal data processing module, a pre-trained visual encoder, a visual projector, a text embedding module and a first large language model; a data set is constructed, and the initial data set takes each visual sequence image and corresponding external information as samples and takes a real speaking text and a correct reasoning process description text as labels; and based on the constructed training set, taking the visual sequence image and the corresponding external information as input, and taking a predicted speaking text and an actual reasoning process description text as output, carrying out iterative training on the initial lip language recognition model until convergence so as to obtain a final lip language recognition model, in the training process, a preset cross entropy loss function is adopted to calculate loss, and parameters of the first large language model, the visual projector and the pre-trained visual encoder are updated based on the calculated loss.

The application discloses an intelligent visual projection method and system suitable for optical imaging, wherein the system comprises a visual stimulation control module for setting a visual stimulation control signal; an image output module for generating full-spectrum visual stimulation and light intensity according to the visual stimulation control signal; a spectrum switching module for receiving the full-spectrum visual stimulation and the light intensity and outputting first specific spectrum visual stimulation; an infrared light source module for outputting infrared spectrum visual stimulation; a spectrum processing module for filtering preset green spectrum signals of the first specific spectrum visual stimulation and integrating the infrared spectrum visual stimulation to output second specific spectrum visual stimulation; and an image stimulation focusing module for fine-tuning the projection area and light intensity of the second specific spectrum visual stimulation and projecting the second specific spectrum visual stimulation to a visual tissue region. The application can solve the problem that the prior art cannot meet the research demand of visual neural optical signals and has the characteristics of intelligence, automation, precision and no optical pollution.

The invention relates to a method for enabling an intelligent robot with a body to look around an aerial view and a storage medium, and the method comprises the steps: reading a feature A4, a feature A3 and a feature A2 through a position encoder, reading internal parameter matrixes of n cameras and an external parameter matrix relative to a main body, and obtaining corresponding BEV information through visual projection transformation; performing feature extraction on a result generated by the position encoder by using two dual-parameter convolution residual modules, and generating corresponding object information and 3D position information according to an extracted feature result; carrying out loss calculation on the corresponding object information and 3D position information and a true value, and carrying out back propagation operation through re-parameter convolution before re-parameter; and carrying out re-parameterization on all the re-parameter convolution to obtain a model for finally generating BEV features. According to the method, coding calculation does not need to be carried out through a transformer technology, and due to the fact that no transformer exists, the method can be deployed on all end-side devices rapidly and universally.

A carwash system and method of operating the carwash system for washing a vehicle is provided. The carwash system comprises a carwash bay, a visual projection assembly to project images and video, an audio output system to emit sound, a user interface having a content menu with a plurality of content selections, a washing unit to conduct a cleaning cycle, and a control unit. The control unit is operatively connected to the visual projection assembly, audio output system, user interface, and washing unit. The control unit synchronizes the visual projection assembly and audio output system with the cleaning cycle conducted by the washing unit based on a specific content selection received from a user input on the user interface.

An electronic device, computer program product, and method provide autonomous projection of a selected viewable content to a second display. The device is configured to, in response to receiving a trigger to project selected viewable content to a selected second display: determine, by evaluating location information of the electronic device and location information of the selected second display, whether the selected second display is located within an acceptable range of and in a line-of-sight of a user of the electronic device; and in response to confirming that the second electronic device is within the acceptable range and in the line-of-sight, initiate a casting of at least the selected viewable content to the selected second display. The device is configured to withhold casting to the selected second display, pending confirmation by a user that the selected second display is the intended device to cast the selected viewable content.

The positioning method, device, medium and equipment for actively adjusting the field of view of visual inertial angle fusion are provided, the feature point relative inertial IMU external parameter rotation matrix in each frame target image of binocular camera calibration is calculated according to current angle information; based on the three-dimensional motion of the target image and the parameters measured by the inertial IMU, a local coordinate system with the initial position of the target image as the origin is established, the corresponding visual projection error vector and the IMU pre-integration residual error vector are calculated based on the feature points and the external parameter rotation matrix of the target image respectively, the factor graph is constructed according to the visual projection error vector and the IMU pre-integration residual error vector, and the state quantity in the factor graph is solved based on the sliding window, and the unmanned aerial vehicle position and the high-frequency unmanned aerial vehicle body pose are determined based on the state quantity; according to the distribution of the feature points in the camera field of view, the camera direction is automatically adjusted, and the positioning method for actively adjusting the field of view of visual inertial angle fusion is solved.

This utility model relates to a tool cutting edge image measurement and chamfering machining machine, including a V-shaped clamp, a clamping seat, a support base, a hand rest, a hand rest adjustment seat, an imaging module, an X-axis moving module, a Y-axis moving module, a Z-axis moving module, and a display. The V-shaped clamp is equipped with a clamping seat for stabilizing the tool. A hand rest is provided on one side of the V-shaped clamp and is mounted on the hand rest adjustment seat. An imaging module for visual projection and detection of the clamping process is located above the V-shaped clamp. The imaging module is mounted and fixed by the X-axis moving module, the Y-axis moving module, and the Z-axis moving module. The imaging module is connected to the display, which is placed on the side of the support base via a display bracket. An angle adjustment component for adjusting the angle of the V-shaped clamp is provided on the support base, and the V-shaped clamp is mounted on the angle adjustment component. This utility model can improve the accuracy of the angle, thereby achieving high-quality machining.

The embodiment of the invention provides a visual inertia angle fusion positioning method and device for actively adjusting a field of view, a medium and equipment. The method comprises the following steps: calculating an external parameter rotation matrix of feature points in each frame of target image calibrated by a binocular camera relative to an inertia IMU according to current angle information; the method comprises the following steps: establishing a local coordinate system taking an initial position of a target image as an original point based on three-dimensional motion of the target image and parameters measured by an inertial IMU, and respectively calculating a corresponding visual projection error vector and an IMU pre-integration residual vector based on a feature point rotation matrix and an external parameter rotation matrix of the target image; constructing a factor graph according to the visual projection error vector and the IMU pre-integration residual vector, solving the state quantity in the factor graph based on a sliding window, and determining the position of the unmanned aerial vehicle and the high-frequency body pose of the unmanned aerial vehicle based on the state quantity; the orientation of the camera is automatically adjusted according to the distribution of the feature points in the field of view of the camera, and the positioning method for actively adjusting visual inertia angle fusion of the field of view is achieved.

This application provides a method, device, medium, program product, and terminal for autonomous driving eye monitoring based on facial projection transformation and visual projection. By acquiring driver image data and driving operation data in real time, and combining facial projection transformation and 3D model construction, the accuracy and reliability of driver state monitoring are significantly improved. It effectively corrects image displacement and distortion caused by driver head movement and posture changes, ensuring accurate facial information recognition. The coarse and fine eye positioning coordinates generated based on facial projection enable accurate monitoring of eye opening and closing in complex situations, thereby identifying driver fatigue. Furthermore, by constructing a 3D head model, the driver's posture at different angles can be analyzed, further enhancing monitoring accuracy. Intelligent warning commands generated by combining driving operation data and eye state can promptly alert the driver to potential safety risks, thereby effectively improving driving safety.

The application discloses a cross-modal data retrieval method, system and device based on a multi-modal knowledge graph. The method decouples features based on a visual feature vector and a structural feature vector, and determines a target visual projection vector. A path constraint contrast learning loss function is constructed based on the target visual projection vector and a text feature vector. A multi-modal knowledge graph is constructed, and effective paths between entities in the multi-modal knowledge graph are mined. The effective paths are encoded into path encoding features, and a multi-scale path perception repulsion loss function is constructed based on the path encoding features. The path constraint contrast learning loss function and the multi-scale path perception repulsion loss function are jointly optimized to determine a target path encoding feature subset. The text feature vector, the target visual projection vector and the target path encoding feature subset are fused to obtain a joint vector. Cross-modal data retrieval is performed based on the joint vector to obtain a retrieval result. The application can improve the accuracy of image-text retrieval.

The invention belongs to the technical field of intelligent measurement and machine vision, and provides a container top surface inclination monitoring method based on a camera visual projection proportion, which realizes lightweight inclination angle calculation without depending on a large-scale training sample and a deep learning model by using top surface projection proportion characteristics under a camera visual angle. Compared with side face inclination measurement in the prior art, the top face inclination measurement method is innovatively provided, accurate monitoring of container top face inclination is achieved through the camera visual projection proportion, and therefore batch recognition and calculation of the top face inclination states of a plurality of containers can be achieved in the mode that the whole container area image is collected; and the monitoring efficiency is greatly improved.

The invention provides an automatic driving data normalization method and system based on topological structure recognition and parameter semantic analysis coupling, and is applied to the technical field of data processing. According to the method, data topological structure reconstruction is completed through directory depth, extended name entropy and regular feature clustering, a logic index is established, and a data role is anchored; extracting calibration parameter metadata, and identifying parameter features and generating analysis codes and operators through large model agent small sample thinking chain reasoning; then, a data processing assembly line is built, an analytic operator is dynamically injected to achieve algorithm coupling, automatic verification is completed through a visual projection alignment effect, relevant rules, logics and operators are iteratively optimized according to a verification result, closed-loop tuning is conducted, and finally, whole-process normalization is conducted on original data, so that the data processing efficiency is improved. And outputting a standardized automatic driving data set with a unified structure and clear parameter semantics.

1. Name of the product in this design: Exercise Bike (Audio-Visual Projection Version). 2. Purpose of this design: a stationary bike for fitness. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the design points: Stereoscopic drawing 1.

The invention belongs to the related technical field of classical poem projection, and particularly relates to a classical poem artistic conception visual projection auxiliary device which comprises a mounting plate, an adjusting assembly is arranged at the lower end of the mounting plate, the lower end of the adjusting assembly is fixedly connected to the upper end of a front-back moving assembly, and a transverse plate is fixedly connected to the lower end of the front-back moving assembly. And a projector main body is arranged at the lower end of the transverse plate. According to the invention, an L-shaped cover plate can be driven to rotate through the mutual cooperation of an electric telescopic rod I, a toothed plate I, a gear I and a rotating shaft until a protective pad arranged on the L-shaped cover plate is in lap joint with a lens arranged at the front end of the projector main body, so that the lens of the projector main body can be shielded and protected; according to the projector, the lens on the projector body can be protected, and the situation that the subsequent projection effect is affected due to the fact that too much dust is adsorbed on the lens when the projector body is not used can be avoided.

The invention discloses an intelligent visual projection method and system suitable for optical imaging, and the system comprises a visual stimulation control module which is used for setting a visual stimulation control signal; the image output module is used for generating full-spectrum visual stimulation and light intensity according to the visual stimulation control signal; the spectrum switching module is used for receiving the full-spectrum visual stimulation and the light intensity and outputting first specific spectrum visual stimulation; the infrared light source module is used for outputting infrared spectrum visual stimulation; the spectrum processing module is used for filtering a preset green spectrum signal of the first specific spectrum visual stimulation and integrating the preset green spectrum signal with the received infrared spectrum visual stimulation to output second specific spectrum visual stimulation; and the image stimulation focusing module is used for finely adjusting the projection area and the light intensity of the second specific spectrum visual stimulation and projecting the second specific spectrum visual stimulation to the visual tissue area. The system can solve the problem that the prior art cannot meet the research requirements of optic nerve optical signals, and has the characteristics of intelligence, automation, precision and no optical pollution.

The application belongs to the technical field of computer vision, and particularly relates to a cross-source point cloud registration method based on visual projection assistance, aiming to solve the problem of low registration accuracy and efficiency of the existing cross-source point cloud registration method affected by data heterogeneity, noise interference and redundant data in non-overlapping areas. The method first performs multi-scale downsampling and feature extraction on the source point cloud and the target point cloud through a KPConv-FPN backbone network, and divides the densest point cloud and the coarse-grained super point cloud; then, a projection mapping from three-dimensional point cloud to two-dimensional image is constructed based on camera calibration parameters, and effective candidate super points are screened to eliminate redundant data; then, PPF features are calculated based on the local densest point cloud, and feature aggregation is completed by combining self-attention and cross-domain attention mechanism, and accurate point pairs are obtained through super point and densest point double-layer matching; finally, the LGR estimator is used to solve the rotation and displacement matrix, and accurate point cloud registration is realized. The application can effectively suppress noise and reduce computational complexity, significantly improve the registration accuracy and robustness of cross-source point cloud, and is suitable for real scene applications such as autonomous driving, robot navigation and three-dimensional reconstruction.

The application discloses a visual projection quick assembly positioning method for large complex components, which is implemented based on a hardware platform of an optical projection system, a positioning system, a control system, a calibration plate and a control computer, and through steps of system deployment, initialization, calibration, digital model import, space alignment, batch projection and step-by-step guidance, CATIA three-dimensional digital model information is projected to the surface of a component to be assembled in a 1:1 proportion, and a traditional serial operation mode of positioning one component at a time is changed, the application can realize parallel guidance of positioning information of multiple components, has the characteristics of one-time calibration reuse, dynamic tracking alignment, color coding distinction and step-by-step operation guidance, can greatly shorten assembly positioning time, eliminate missed assembly, improve production flexibility, and is suitable for assembly of large complex components such as airplanes, automobiles and ships, and is especially suitable for quick positioning and installation of 79-frame and 80-frame supports of C919 airplanes.

The invention discloses a valve hall equipment identification method based on multi-scale feature fusion and semantic matching, and the method comprises the steps: collecting a valve hall image, and carrying out the preprocessing of the image; and inputting the preprocessed image into a multi-scale feature extraction network based on a feature pyramid network to generate a multi-scale visual feature map. Constructing an equipment identification model, training a visual projection module and a semantic projection module in an end-to-end manner through an alignment training mechanism based on adaptive dynamic contrast learning, generating equipment category information through a region identification module based on the trained visual projection module, and combining a visual feature vector and the category information as input of a positioning module; and performing segmentation task training. And constructing structured text semantic description for each device of the valve hall, generating semantic feature vectors through a semantic projection module, constructing a semantic knowledge base, and realizing visual-semantic matching recognition. The method can effectively solve the problems of large scale difference of valve hall equipment, complex environment, insufficient semantic understanding and the like, and improves the recognition precision and robustness.

An immersive crystal ball 3D visual projection device is provided, including: a hemisphere body serving as the projection image carrier, featuring a mounting surface and an outer spherical surface; a mounting base with a hemispherical hollow shell structure, connecting with the hemisphere body to form a complete sphere; wherein the mounting base includes a mounting cavity housing a display screen and a control unit, with the display screen's viewing surface facing the mounting surface to project images within the hemisphere body, enabling external observers to view the projected images through the outer spherical surface; and the control unit includes a display control board and a power control board, the display control board is electrically connected to the display screen to transmit image signals to it; the power control board is connected to a battery and is electrically linked to the display control board for power distribution and information exchange.

The invention discloses a mechanical equipment AR (Augmented Reality) real-time tracking maintenance method based on YOLOv11 and coordinate transformation. The method comprises the following steps of collecting equipment operation data through a sensor and evaluating a health state; acquiring an image through an AR equipment camera and transmitting the image to a server; the server calls a YOLOv11 model to carry out equipment identification, and outputs an equipment category and a pixel coordinate; establishing a transformation matrix through a calibration process, and converting the image coordinates into AR equipment display coordinates; and finally, fusing the state information with the display coordinates, and carrying out visual projection in a virtual-real superposition form through AR (Augmented Reality) equipment. The invention further discloses a real-time tracking maintenance system which comprises a state monitoring module, an equipment identification module and a data visualization module. Through fusion of YOLOv11 high-precision target detection, coordinate transformation and multi-source data interaction, the problems that an existing AR maintenance system is poor in equipment recognition robustness, inaccurate in space registration and disjointed with underlying monitoring are solved, and real-time, accurate and visual intelligent maintenance of the equipment state is achieved.

The invention discloses a visual auxiliary loopback method based on semantic segmentation and visual projection transformation, and the method comprises the steps: obtaining a robot visual image, and extracting the semantic segmentation features, feature points, and feature point descriptors of the robot visual image through a multi-task neural network based on a residual structure trunk; performing dynamic object elimination and edge feature point screening on the current frame image based on the semantic segmentation features and the feature points to obtain edge feature points and corresponding descriptors thereof; performing semantic similarity rapid retrieval on the edge feature points of the current frame and a historical frame library, and performing fine matching based on edge feature point descriptors to obtain an optimal loopback candidate frame; performing matching and transformation matrix estimation on the semantic consistency edge feature points of the current frame and the optimal loopback candidate frame, verifying loopback by combining semantic and geometric standards, and outputting positioning correction.