13 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.

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 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.

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.

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 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.

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.