150 results about "Texture mapping" patented technology

The invention relates to the technical field of image processing, in particular to a drainage pipeline defect three-dimensional quantification method and device based on vision, and the method comprises the steps: carrying out the at least one processing of sparse point cloud reconstruction, dense point cloud reconstruction, grid reconstruction, texture mapping and scale calibration of a collected visual image, obtaining a real three-dimensional model of the drainage pipeline; calculating a central point of the drainage pipeline based on the real three-dimensional model, and calculating a central line of the drainage pipeline according to the central point; and based on the center line, identifying at least one actual defect of a staggered joint defect, a disjunction defect, a fluctuation defect and a deformation defect of the drainage pipeline, so as to output actual defect information of the drainage pipeline according to the at least one actual defect. Therefore, the problems of incomplete identification or misjudgment of information such as cracks, leakage and sediments and the like caused by low efficiency and detail missing due to relatively great influence of manual subjective judgment or sparse laser point cloud in related technologies are solved.

The embodiment of the invention discloses a three-dimensional landform model reconstruction method and device based on geometry and texture combination. A specific embodiment of the method comprises the following steps: carrying out self-adaptive grid division on a landform three-dimensional point cloud and then carrying out geometric super-resolution to obtain a target three-dimensional landform sub-grid; performing color texture mapping and texture correction enhancement on the target three-dimensional landform sub-grids to obtain an enhanced landform texture map; performing collaborative bidirectional optimization on the enhanced landform texture map and the target three-dimensional landform sub-grids to obtain a super-resolution landform texture map and a super-resolution three-dimensional landform sub-grid; performing model recombination and fusion on the plurality of super-resolution landform texture maps and the plurality of super-resolution three-dimensional landform sub-grids to obtain a three-dimensional texture landform grid model; and performing density control reconstruction processing on the three-dimensional texture landform grid model to obtain a three-dimensional density texture landform model, and storing the three-dimensional density texture landform model. According to the embodiment, the quality of the three-dimensional density texture landform model can be improved, and waste of storage resources is reduced.

The invention relates to the technical field of virtual reality cultural relic construction, in particular to a cultural relic three-dimensional construction VR display system based on multi-modal data fusion. The specific implementation process comprises the steps of obtaining a laser point cloud and a two-dimensional image of the surface of a cultural relic, respectively generating a geometric point cloud and a visual sparse point cloud, and inputting the geometric point cloud and the visual sparse point cloud into a modal registration model based on geometry-luminosity combined constraint to complete pixel alignment and data fusion; performing texture mapping by using a Markov random field to generate a three-dimensional mapping model, generating a feature saliency map based on curvature calculation, and performing differential mesh simplification on flat and detail areas to output a polygonal contour; and generating a normal and a replacement map by using a ray casting algorithm, and importing the normal and the replacement map into a virtual reality engine for rendering display in combination with the polygonal contour. According to the method, a multi-mode joint optimization and differentiation grid simplification technology is utilized, dislocation and ghosting of texture mapping are effectively eliminated, and while VR rendering fluency is guaranteed, microscopic geometric details and physical material attributes of cultural relics are reserved.

A method of video processing is provided. The method may include inputting attribute data and a sparse-depth map associated with an image area into a sparse-depth completion network. The method may include generating a refined dense-depth map based on the attribute data and the sparse-depth map using the sparse-depth completion network. The method may include performing a three-dimensional (3D) reconstruction procedure based on the refined dense-depth map to generate a point cloud of the image area. The method may include performing a triangular-meshing procedure to generate a mesh model based on the point cloud of the image area. The method may include performing a texture-mapping procedure based on the mesh model and the attribute data to generate a textured mesh of the image area. The method may include performing a vertex-normal procedure based on the textured mesh to generate a 3D representation of the image area.

The invention belongs to the technical field of three-dimensional modeling, and discloses a city building three-dimensional model refined construction method based on oblique photography. Comprising the steps of collecting inclined image data of a to-be-modeled urban area and performing data cleaning to obtain a modeling image data set; carrying out projection consistency analysis, identifying a boundary dislocation region and removing the boundary dislocation region to obtain a dislocation removal data set; shielding area identification is carried out, shielding compensation is carried out based on an identification result, and an enhanced three-dimensional point data set is output; executing detail reservation to obtain a triangular facet data set; normal optimization is carried out, plane adjustment is carried out on the triangular surface data set based on an optimization result, and a three-dimensional grid data set is obtained; constructing an initial three-dimensional model, and performing map mapping on the initial three-dimensional model to obtain a detail map set; constructing a fine building three-dimensional model in combination with the detail map set and the initial three-dimensional model; and the boundary definition, the structural integrity and the texture fineness of the urban building three-dimensional model are improved.

The invention provides a photogrammetry integrated control method and system, and relates to the technical field of photogrammetry control, and the method comprises the steps: obtaining multi-source original data, such as a sequence image, an initial point cloud and a real-time attitude parameter; carrying out combined preprocessing of timestamp alignment, point cloud denoising and image distortion correction, and uploading key logs and quality indexes through a consensus mechanism for evidence storage; performing bundle adjustment to solve internal and external orientation elements, and calling block chain historical control points for verification and dynamic adjustment; generating an initial three-dimensional point cloud through dense matching; verifying the point cloud precision by using a high-precision check point, and feeding back a correction instruction when the point cloud exceeds the limit; gridding and texture mapping are carried out on the effective point cloud to generate a three-dimensional model, and achievements are partitioned and stored in edge nodes and are chained for evidence storage; the system comprises a multi-source data acquisition module, a data preprocessing module, an adjustment resolving module, a point cloud generation module, a point cloud verification module and a three-dimensional modeling module. The efficiency, precision and reliability of photogrammetry are effectively improved.

The invention relates to an electric field visualization real-time monitoring system and method, belongs to the technical field of electric field visualization, and is used for solving the problems of insufficient real-time performance, large measurement interference, incomplete imaging, weak multi-user cooperation and lack of unified time reference in the prior art. The method comprises the following steps: acquiring electric field scattering data of a test body by a conformal optical fiber electric field sensor array, transmitting the electric field scattering data to an edge GPU node through a plastic optical fiber-CAN-FD link, and converting the electric field scattering data into electric field amplitude data; the edge GPU node is combined with WebGL3D texture mapping and a volume ray casting algorithm to complete volume rendering, and multi-user concurrent interaction is realized through a Web server and a browser client; and a White-Rabbit clock architecture is adopted to provide a unified time reference for the whole process. According to the method, dynamic and accurate capturing of the electric field is achieved, and the multi-user concurrent access requirement is effectively met.

One or more embodiments of the invention provide a three-dimensional model generation method, apparatus and device, a medium and a program product. The method is applied to CAD software and comprises the following steps: acquiring a plane image and a model thickness of a modeling object; generating a plane grid for the modeling object according to the plane image; generating a front grid, a back grid and a side grid for the modeling object according to the plane grid and the model thickness; and combining the front grid, the back grid and the side grid into a three-dimensional grid, and mapping the texture of the plane image to the three-dimensional grid to obtain a three-dimensional model of the modeling object.

The invention provides a three-dimensional modeling method and system based on multi-source heterogeneous data, and relates to the technical field of three-dimensional reconstruction. Multi-view point clouds, images and environment data in the same time state are obtained, and point cloud alignment precision is enhanced through feature detection and descriptor matching; an iterative nearest point algorithm is utilized to complete initial point cloud fusion to generate a three-dimensional model, position calibration is realized in combination with geometric features of environmental data, triangular meshes are divided by adopting a triangulation algorithm, surface defects of the model are repaired by adopting a hole filling algorithm, camera calibration is performed on image data, the image data are projected to the corresponding triangular meshes, and the three-dimensional model is obtained. And setting a pixel boundary threshold value to control a projection position, realizing accurate texture mapping, and defining a degradation coefficient to evaluate a local deformation condition of the three-dimensional model. According to the method, by fusing multi-source heterogeneous data and combining feature matching, position calibration and degradation coefficient evaluation, high-precision and complete three-dimensional model construction is achieved.

The invention relates to the technical field of environment modeling, in particular to an underground safety production simulation modeling method based on the VR technology, and the method comprises the steps: obtaining all RGB images of an underground scene and corresponding depth images, and the attitude information and position coordinates of a camera when each frame of RGB image is shot, so as to generate a dense point cloud, and constructing a triangular mesh model; calculating the screening value of each point cloud, and obtaining the feature point cloud of each triangular patch; and obtaining all candidate images of each triangular patch, determining a mapping deviation value, a texture distortion degree and a quality evaluation value of each triangular patch in each candidate image, screening the candidate images of each triangular patch, performing texture mapping on the triangular mesh model, and importing the texture mapping result into a VR engine to construct a virtual underground environment. According to the method, the overall effect of texture mapping of the model can be improved, so that a highly vivid virtual underground scene is constructed, and the immersion and reality of underground scene safety production virtual practical training are enhanced.

The embodiment of the invention provides a model processing method and device, and relates to the technical field of model editing processing. Comprising the following steps: acquiring an initial object model, a first image set, a target image and camera internal and external parameters corresponding to each image in the first image set; the target image is an image obtained by performing special effect processing on an image of a target object; obtaining an initial part model of the target object according to the initial object model, the first image set and the camera internal and external parameters corresponding to each image in the first image set; acquiring a fitting part model according to the initial part model, the target image and camera internal and external parameters corresponding to a first image in the first image set; deforming the initial object model based on the fitting part model to obtain a fitting object model; and mapping the fitting object model based on the target image to obtain a target object model. The embodiment of the invention is used for improving the efficiency of carrying out special effect editing on the three-dimensional model.

The application discloses an infrared image generation method and system based on a physical prior constraint generative adversarial network, relates to the field of infrared image generation, and aims to solve the problems of insufficient physical reality and lack of representation ability of infrared radiation characteristics of the existing infrared image generation method. The application first designs a physical prior knowledge learning network, which is used to learn the prior representation related to the infrared radiation characteristics from the infrared image, and realizes the prediction of the infrared radiation related parameters through a deep learning network. Secondly, a generative adversarial network based on the physical prior constraint is designed based on the proposed physical prior knowledge learning network, the physical prior features are introduced into the image generation process, and the learning ability of the generator to the overall distribution of the infrared radiation and the representation ability of the generator to the infrared radiation characteristics are enhanced. The method breaks through the limitation that the traditional generator only relies on shallow texture mapping. The application is suitable for the fields of visible light to infrared image generation, infrared vision algorithm research and development.

The present disclosure relates to a flood simulation method and system. The method and system calculate flood prediction data of a target scene, such as water flow direction and water flow intensity, by presetting a flood simulation model; perform water flow texture mapping on the target scene according to the flood prediction data to obtain a water flow simulation layer; and perform layering rendering on the water flow simulation layer and a scene floor of the target scene to obtain a flood simulation image of the target scene. Compared with the simulation calculation result directly output by a related model, the flood simulation image can provide a real flood simulation visual effect, facilitate observation and decision-making of relevant personnel, and reduce the professional requirements for the relevant personnel. In addition, the method and system realize seamless connection between the simulation calculation stage and the simulation rendering stage, can guarantee the real-time performance of the simulation, and facilitate timely output and updating of the simulation result.

The invention relates to the technical field of XR operation, and discloses a WebXR-based panoramic immersive robot teleoperation system and method. The method comprises the following steps: carrying out distortion correction and splicing fusion on original images collected by a double-fisheye lens to obtain a panoramic image frame; encoding the panoramic image frame into a video code stream, transmitting the video code stream to a browser end, and decoding the video code stream at the browser end to obtain a panoramic video texture; mapping the panoramic video texture to the inner surface of a sphere, setting a virtual camera at the center of the sphere, and constructing a panoramic sphere rendering model; and converting the attitude quaternion of the VR head-mounted display into a sight decoupling rotation matrix, performing local GPU rendering on the panoramic sphere rendering model to obtain a real-time visual angle picture, and mapping a rocker shaft value of the gamepad into a control instruction to be sent to a robot dog end. In the whole view angle switching process, vertex transformation and texture sampling are completed at the browser end, no pan-tilt rotation instruction is generated or sent to the robot dog end through the network, and delay is reduced.

Systems and methods of attribute transfer between mesh models for use in mesh coding. In a method according to some embodiments, a source point cloud is obtained from a source mesh model. For each of a plurality of source points in the source point cloud, an attribute is obtained based on a source texture map associated with the source mesh model. A destination point cloud is obtained from a destination mesh model. For each of a plurality of destination points in the destination point cloud, an attribute is obtained based on the attribute of one or more source points of the source point cloud. Attributes of pixels in a destination texture map are set based on the attributes of points in the destination point cloud.

This invention relates to a method for UAV flight path planning based on a 3D reality model, comprising the following specific steps: 3D reality modeling based on oblique photogrammetry, specifically including data acquisition planning, image preprocessing, aerial triangulation, dense matching, and texture mapping; and flight path planning based on the 3D reality model, specifically including importing the 3D model, setting the task area, setting flight parameters, and obstacle avoidance and safety settings. Through the deep integration of 3D reality modeling and intelligent flight path planning, safety and efficiency are improved. The high-precision 3D model generated using oblique photogrammetry technology can intuitively display three-dimensional information such as terrain undulations and obstacle distribution, enabling the UAV to autonomously avoid obstacles in complex environments and reducing collision risks. Dynamic optimization of the flight path through quantitative parameters improves operational efficiency and data acquisition completeness. Flight parameters can be quickly adjusted to adapt to different task requirements, ensuring operational safety while improving data quality and operational efficiency.

The application relates to the technical field of image processing, in particular to a visual-based three-dimensional quantification method and device for defects of a drainage pipeline, wherein the method comprises the following steps: at least one of sparse point cloud reconstruction, dense point cloud reconstruction, grid reconstruction, texture mapping and scale calibration is performed on collected visual images to obtain a real three-dimensional model of the drainage pipeline; based on the real three-dimensional model, the center point of the drainage pipeline is calculated to calculate the center line of the drainage pipeline according to the center point; and based on the center line, at least one actual defect of the drainage pipeline is identified from the following defects: a joint defect, a disconnection defect, a fluctuation defect and a deformation defect, so that actual defect information of the drainage pipeline is output according to the at least one actual defect. Therefore, the problems of low efficiency, missing details, incomplete identification of cracks, leakage and sediments and misjudgment caused by the fact that the related art is greatly affected by artificial subjective judgment or laser point clouds are solved.

The embodiment of the invention discloses a cloth animation rendering method and device, equipment, a medium and a product, and relates to the technical field of games. The method comprises the steps of obtaining pre-generated first texture mapping data; sampling from the first texture mapping data according to the playing progress of the cloth animation to obtain vertex coding data corresponding to each cloth grid vertex in the current to-be-displayed animation frame, and decoding the vertex coding data corresponding to each cloth grid vertex in the current to-be-displayed animation frame; the vertex data corresponding to the vertexes of the cloth grids in the current to-be-displayed animation frame are obtained and then rendered to generate the current to-be-displayed animation frame, the vertex data can be obtained only through texture sampling and decoding operation, and resource consumption during client running is reduced. The high fidelity of the animation is guaranteed, meanwhile, the animation production period is shortened, the resource consumption, the production cost and the maintenance cost of the cloth animation are reduced, batch processing can be conducted on a large number of cloth animations, and the applicability is improved.

The invention relates to the field of image processing, and provides an image generation method, electronic equipment and a vehicle, and the method comprises the steps: obtaining a fisheye image corresponding to the current position of the vehicle, projecting each pixel point in the fisheye image to a preset spherical model, and determining a first projection point corresponding to each pixel point; projecting each first projection point to a preset cylinder model to obtain a second projection point corresponding to each first projection point; and obtaining target internal and external parameter data corresponding to the fisheye image, and performing texture mapping processing on all the second projection points according to the target internal and external parameter data to obtain a planetary visual angle top view corresponding to the current position of the vehicle. The fisheye image is sequentially projected twice through the spherical model and the cylinder model, alignment of ground textures is achieved due to the fact that the radius of the bottom face of the cylinder is large, points far away from the center can be compressed through vertex transformation of the spherical model, and therefore the problem that far ground points are seriously stretched is avoided, and the accuracy of ground texture alignment is improved. And the accuracy of the planetary view angle top view is improved.

The application relates to the field of intelligent manufacturing and printing processes, and discloses a digital printing equipment image optimization system based on dynamic texture mapping, which comprises the following steps: constructing a dynamic manifold representation space of printing parameters, realizing global optimization through a curvature-driven quantum annealing algorithm; designing an online correction mechanism of a connection coefficient and a multistage fault-tolerant protocol, establishing a differential homeomorphism mapping from quantum optimization results to execution instructions; extracting optimization features by using a manifold adaptive wavelet transform, and combining deep reinforcement learning to generate pulse shaping control quantities. The method breaks through the local extremum limitation of traditional optimization, realizes adaptive control under material property drift, solves the control mismatch problem caused by multi-physical field coupling, and improves the precision stability and working condition adaptability of complex texture printing.

A method of rendering a stereoscopic image of an object is described. The stereoscopic image comprises a left image and a right image. The method comprises initialising a computer model of the object (200) and a texture mapping for rendering the computer model with a texture. The method comprises the steps of receiving a first image of the object from a first image sensor (14a), receiving a second image of the object from a second image sensor (14b), receiving head tracking data of the observer (360), determining one or more render camera viewpoints relative to the computer model based on the head tracking data, and rendering the stereoscopic image based on the computer model and the texture mapping using the one or more render camera viewpoints, wherein the left image of the stereoscopic image is rendered using the first image as the texture and the right image of the stereoscopic image is rendered using the second image as the texture.

The application provides a video texture mapping and real-time rendering method and system based on a digital twin scene, relates to the technical field of digital twin rendering, and comprises the following steps: acquiring a real scene monitoring video stream and performing real-time image content analysis; dividing the texture details of different regions of the video stream according to the features and numerical values of the image analysis and generating region detail identifiers associated with the video content; identifying the dynamic features of the video picture based on the identifiers and generating scene state codes representing the comprehensive picture conditions; dynamically selecting a target engine and corresponding rendering quality parameters from preset heterogeneous rendering engines in combination with the current load state of a graphics processor; and mapping the video stream image data to the surface of a corresponding model of the digital twin scene as dynamic texture to realize efficient rendering of the picture, so that dynamic texture mapping and adaptive real-time rendering based on video content analysis and hardware load in the digital twin scene can be realized.

The invention relates to the technical field of slope engineering modeling, and discloses a slope structural surface unmanned aerial vehicle point cloud fusion refined modeling method, which comprises the following steps: acquiring slope global point cloud data and optical images through an unmanned aerial vehicle carried high-precision positioning system, combining local point cloud data acquired by a handheld laser scanner, calibrating and pre-processing, and obtaining a slope global point cloud model; a point cloud normal vector is determined based on a local plane fitting technology, structural boundary information is extracted through a normal vector difference boundary detection algorithm, structural plane clustering segmentation is completed by adopting a region growing algorithm, finally, a triangular mesh model is generated, texture mapping and hierarchical simplification are performed, and refined modeling of a slope structural plane is realized. According to the method, the modeling precision and efficiency are improved, and reliable model support is provided for stability analysis and risk assessment of slope engineering.

This invention relates to the fields of computer graphics and 3D modeling optimization technology, specifically to a lightweight 3D model method and system based on point cloud layering and dynamic texture mapping. In use, this invention establishes a bidirectional coupling mechanism between point clouds and textures, thereby improving storage efficiency, rendering performance, and visual fidelity. Regarding storage efficiency, it relies on texture curvature adaptive segmentation and dynamic slicing binding technology to construct an efficient associative storage system for geometry and texture, achieving excellent geometry and texture compression effects and significantly reducing the storage cost of high-precision 3D models. In terms of real-time rendering performance, it significantly improves real-time model scheduling efficiency through runtime dynamic loading strategies combined with efficient visibility filtering acceleration and intelligent resource preloading technology, thereby significantly improving work efficiency in scenarios such as design iteration and model editing.

The invention discloses an orthophoto real-time generation and three-dimensional reconstruction method based on an aerial image, and the method comprises the steps: obtaining an aerial image sequence, and carrying out the monitoring of an air route; in the real-time reconstruction stage, the aircraft executes flight actions of flying to a waypoint and collecting images, the airborne embedded equipment continuously obtains original images shot by the camera load, and the original images are zoomed according to the reconstruction precision set by a user; synchronously constructing a three-dimensional model of a sparse scene by adopting an incremental SFM; executing real-time orthoimage generation, and synchronously uploading results to a remote server for a user to preview on a terminal; in the post-processing reconstruction stage, when the aircraft arrives at the last waypoint and no new image data exist, the route is switched to a task completion state, the aircraft returns, and the three-dimensional model of the sparse scene obtained in the real-time reconstruction stage is used for executing SFM global optimization and MVS-based dense reconstruction and texture mapping to generate a final three-dimensional model. And the final reconstruction results are uploaded in a centralized manner.

The application relates to an OpenGL multi-class object uniform drawing method based on VBO internal coding, which comprises the following steps: constructing a mixed data structure containing vertex coordinates, color components, texture coordinates and object type marks, and storing the mixed data structure in the memory of a VBO in an interlaced arrangement; defining a uniform vertex shader and a fragment shader; judging whether texture mapping is needed according to the object type marks during a rendering process; and deleting the VBO object and the shader program after the rendering is completed, and releasing the display memory and the memory resources. The application links map elements with different rendering logics, realizes the uniform drawing of heterogeneous objects under a single pipeline, fully utilizes the parallel processing capacity of a GPU, avoids frequent switching of the shader, effectively saves the communication bandwidth between a CPU and the GPU, simplifies the development difficulty of multi-map element mixed rendering in a complex scene, and facilitates the horizontal expansion of a system in large-scale geographic information visualization.

This invention discloses a transferable adversarial texture coating generation method and system. The scheme includes a multi-model collaborative training section, establishing a source model and target model collaborative training and two-layer optimization mechanism. The inner layer introduces target feature perturbations to generate adversarial camouflage samples, while the outer layer employs weighted average loss and transferability regularization constraints, enabling the adversarial texture coating to have transferability across detector models and target carriers. In the feature space alignment section, feature layers of different architecture models are matched, and dynamic feature layer matching and multi-scale gradient alignment loss functions are calculated to achieve consistent alignment calibration of shallow and deep feature spaces. A transferability evaluation index is introduced during the alignment process to evaluate the alignment effect in real time. In the three-plane mapping texture generation section, target geometric features are extracted, surface curvature distribution regions are calculated, dynamic weights are assigned to different regions, and weighted fusion texture generation is performed to achieve accurate texture mapping and coverage of the adversarial texture coating on complex three-dimensional surfaces of different target carriers.

This invention relates to the field of tunnel detection and identification technology, specifically a method for detecting defects in water diversion tunnels based on a 3D model. The method includes: collecting laser point cloud data, panoramic image sequences, and ground-penetrating radar (GPR) profile data of the target water diversion tunnel section to form a multi-source detection data set. A 3D mesh model of the tunnel structure is reconstructed using the laser point cloud data. The panoramic image sequence is mapped onto the model to generate a textured 3D model. Abnormal signal segments from the GPR profile data are identified to obtain a set of radar anomaly depth markers, which are then projected onto the textured 3D model to construct a 3D detection model with defect markers. Candidate defect regions are extracted through region growing and segmentation. The opening width and extension length of each candidate defect region are quantified. Based on geometric features, the defect type is classified, and a defect detection report is output. This method achieves the fusion and correlation of multi-source detection data in 3D space, completing automatic defect region segmentation and geometric feature quantification.

The invention provides an industrial vision intelligent online detection system for texture flaws of fiber products, which relates to the technical field of industrial machine vision and is characterized in that a spatial transformation network is introduced, differentiable geometric adaptive calibration is carried out on continuously acquired image streams, distorted fabric textures are mapped to a standard space, and the texture flaws of the fiber products are detected. And interference of physical deformation on detection is effectively eliminated. On this basis, a flawless ideal texture reference is generated by using a random block mask and pyramid feature reconstruction mechanism, and gradient sensing type adaptive difference calculation is performed on the calibrated image and the reconstructed image in combination with a texture gradient field of a reconstruction domain. And finally, accurately restoring the abnormal thermodynamic diagram of the calibration domain to a physical coordinate system through a reverse re-projection technology of a transformation grid, thereby realizing high-precision and anti-interference online detection of fine texture flaws on the surface of the fiber product in a dynamic deformation environment.