3029 results about "3D modeling" patented technology

A modeling method for three-dimensional real-time measurement reconstruction, comprising: on the basis of a three-dimensional camera, a laser radar, and an infrared sensor device, generating a multi-source original data set; performing data preprocessing; performing feature extraction and data fusion; performing three-dimensional space construction; by means of a deep machine learning algorithm, performing real-time dynamic adjustment and optimization on a model; and, by adopting an advanced image processing algorithm, generating a high-precision three-dimensional model.

A system for UAV collaborative coverage path planning based on a Q-learning adaptive ant colony algorithm including a memory, an image collection device, and a plurality of UAVs loaded with a path planning module configured to: construct a 3D model in a collaborative coverage environment, by performing a cell division on the 3D model based on a scanning range of an airborne radar of each UAV, obtain one or more sub-regions; by establishing constraints of the UAV and the environment based on the determined 3D model of the region to be searched, establish a problem total cost model; perform a plurality of rounds of iterations, calculate a reward value of each ant colony and determine whether a maximum iteration count is reached, if the maximum iteration count is reached, enter a new round of iteration, otherwise, output a path corresponding to a current round of iteration as a final path.

The invention discloses a digital twin three-dimensional scene modeling method based on a webGPU, and relates to the technical field of three-dimensional scene modeling and graphic computing, multi-source sensing data are asynchronously sampled from sparse point cloud, a video texture sequence, a scene semantic tag graph and a structure boundary tuple, and a six-dimensional structure unit group is generated through a normalization operator; constructing a structural unit atlas with nodes representing component entities and edges representing constraint relations, and introducing a tension balance mechanism and multi-scale constraints to generate a modeling path prior model; constructing a graph calculation and graph rendering dual-channel assembly line in the WebGPU, and executing parallel texture mapping and boundary fitting operation; a dynamic sensing module is used for capturing scene disturbance and driving atlas response, and incremental reconstruction of the model is achieved; and finally, mapping the model to a Web terminal, and supporting microscopic semantic query and multi-layer data linkage. According to the method, the response speed, semantic consistency and structural adaptability of three-dimensional modeling in a complex environment are improved.

Methods and systems are described for 3D modeling and visualization of a patient's facial structure and features for dental treatment planning.

Provided are a processing system for a three-dimensional model, a method for obtaining a physical model on the basis of three-dimensional printing of a three-dimensional processing system, a system for generating a three-dimensional model from a virtual reality / augmented reality three-dimensional sketch, a diffusion model training method, and a method for editing a three-dimensional model on the basis of a virtual reality / augmented reality three-dimensional sketch. The method for obtaining a physical model on the basis of three-dimensional printing of a three-dimensional processing system comprises: step one, at an input apparatus, a user using a hand or a handle to draw three-dimensional sketch content in the air, wherein a three-dimensional sketch is stored in the form of a three-dimensional point cloud, and when the user draws a trajectory, a corresponding point cloud is generated in the drawn trajectory and is displayed in a three-dimensional virtual space in a highlighted manner, and displacement and deletion operations of the user for the three-dimensional sketch are overall displacement and deletion operations for points in a region corresponding to the point cloud of the three-dimensional sketch; step two, a computing apparatus converting the three-dimensional sketch content into a three-dimensional model; step three, converting the three-dimensional model into a readable file for an execution apparatus, wherein the conversion is implemented by using a slicing algorithm; and step four, a three-dimensional printer executing the readable file to perform a printing operation, so as to obtain a physical model.

The invention provides a three-dimensional modeling processing method based on unmanned aerial vehicle oblique photography. The method is applied to the technical field of three-dimensional modeling, and comprises the following steps: obtaining a serialized image set containing geographical coordinate information according to original image data collected by an oblique photography camera carried by a multi-rotor unmanned aerial vehicle; according to time-space synchronization parameters of the serialized image set, determining a multi-view image matching relation matrix with an overlapping degree quantitative index; determining mixed three-dimensional point cloud data fusing sparse point cloud and dense point cloud according to geometric constraint conditions of the multi-view image matching relation matrix; determining an initial three-dimensional grid model with multi-level details according to the topological connection relationship of the mixed three-dimensional point cloud data; and determining an optimized three-dimensional model based on adaptive texture mapping according to the surface curvature distribution characteristics of the initial three-dimensional mesh model. In this way, the efficiency of three-dimensional modeling can be improved.

The invention relates to the technical field of image super-resolution enhancement, in particular to a tablet computer image super-resolution enhancement method based on a generative adversarial network. The method comprises the following steps: collecting an image through a tablet computer, and carrying out regional illumination component calculation on the image to obtain detailed illumination component data; secondly, quantizing the motion out-of-focus fuzzy degree based on the illumination data, generating track fuzzy intensity sensing data, performing 3D modeling by combining the data, and estimating the distortion trend of the image; then, a shooting error is eliminated by using rendering visual angle distortion correction, a more real visual angle effect is generated, and super-resolution enhancement is performed on the image by using a generative adversarial network, and image details are improved. And finally, designing automatic firmware based on the super-resolution enhanced data, and embedding the automatic firmware into a tablet computer control system. According to the method, the image super-resolution enhancement technology is optimized, so that the image super-resolution enhancement technology is more perfect.

The invention provides a game cartoon character display method based on a virtual reality technology. The method comprises the following steps: acquiring three-dimensional model data of a game cartoon character in a target display area through a user interaction terminal; the virtual reality content management platform determines a dynamic rendering precision level according to the model data, and generates a real-time rendering strategy including a model patch reduction coefficient, a texture compression rate and a skeleton animation updating frequency in combination with terminal performance parameters; the strategy is sent to a virtual reality supervision platform and a user interaction terminal, and a virtual reality rendering engine platform is instructed to execute real-time rendering; and the virtual reality supervision platform monitors the frame rate fluctuation data of the head-mounted display device, calculates the scene rendering stability, sends a rendering optimization instruction if the scene rendering stability is lower than a threshold value, and adjusts the model data acquisition frequency and the video memory cleaning period to optimize the performance. The rendering efficiency and the system stability can be improved, and the hardware load and the frame rate fluctuation are reduced.

The invention relates to the field of computer vision and industrial safety monitoring, and discloses a pipe gallery pipeline key connection point leakage monitoring system and method based on AI vision, and the system comprises a data collection module, an intelligent analysis module, a 3D modeling module, a space-time verification module and an alarm prediction module. Real-time detection and three-dimensional accurate positioning of a leakage area are realized in combination with neural network optimization driven by physical simulation parameters; further through optical flow tracking and fluid mechanics verification, false alarm events of non-physical rules are screened out; and based on Bayesian decision and diffusion equation prediction, generating a leakage risk heat map and triggering graded alarm. The method solves the technical problems of low leakage detection precision, high false alarm rate and inaccurate positioning in a complex pipe gallery scene, has the advantages of high environmental adaptability, high anti-interference capability and prospective risk pre-judgment, and is suitable for intelligent safety monitoring of underground pipe galleries and petrochemical engineering pipelines.

The invention relates to the technical field of coal mine disaster monitoring, in particular to a gas coal mine goaf coupling disaster monitoring method, an electronic device and a storage medium, and the gas coal mine goaf coupling disaster monitoring method comprises the following steps: obtaining comprehensive data of a goaf through a sensor network, and carrying out data preprocessing to obtain standardized data; constructing a digital twinborn model through a 3D modeling and geographic information system technology; performing data synchronization and model correction processing on the digital twinborn model, and optimizing parameters and states of the digital twinborn model; constructing a fluid-solid-heat multi-field coupling model through a computational fluid mechanics and finite element analysis method; constructing a risk assessment model through an analytic hierarchy process and a fuzzy comprehensive evaluation method; training a disaster early warning model by using a machine learning algorithm based on the standardized data and the risk assessment model; a digital twinborn model, standardized data, a risk assessment model and a disaster early warning model are integrated, and a visual interaction platform is constructed. According to the monitoring method, multiple disaster elements can be coupled and dynamically evolved, and the disaster prediction accuracy and timeliness are greatly improved.

The invention discloses an airspace engine 3D printing deformation compensation method. The method comprises the following steps that S1, a three-dimensional CAD model is constructed, and a printing layer set is generated; s2, obtaining residual stress tensor fields of the current printing layer and the historical printing layer; s3, constructing a stress shadow mapping tensor; s4, inputting the stress shadow mapping tensor and the current printing layer parameter into the reverse stress propagation neural network model, and outputting a deformation prediction vector field; s5, performing geometric compensation processing on the geometric area of the printing layer according to the deformation prediction vector field; s6, generating a printing code according to the compensated geometric model; and S7, carrying out error comparison on the actual deformation vector field and the overall prediction deformation vector field, if the error is greater than a preset tolerance threshold value, feeding back error information to the step S5, and repeatedly executing the steps S5 to S7 until the error vector field does not exceed the tolerance threshold value. According to the method, residual stress modeling and the reverse stress propagation neural network are fused, and 3D printing deformation compensation of the airspace engine is achieved.

The invention relates to an air-ground integrated bridge disease monitoring method and an application system thereof, and the method comprises the steps: controlling an unmanned plane to take off from a nest, and transmitting a bridge initial inspection task to the unmanned plane; sending the bridge image data to a vehicle-mounted high-performance edge server for primary three-dimensional modeling; carrying out monomer splitting on the general three-dimensional model of the bridge, and carrying out close photogrammetry on the bridge by an unmanned aerial vehicle based on a close inspection route to obtain a monomer high-resolution image of each part of the bridge; the unmanned aerial vehicle automatic inspection and data processing platform executes disease target detection and disease semantic segmentation on the single high-resolution images; and associating and binding disease target detection and disease semantic segmentation results with the bridge refined three-dimensional model to generate a bridge disease detection report. A worker only needs to draw an inspection area, and the unmanned aerial vehicle automatic inspection and data processing platform automatically generates an unmanned aerial vehicle inspection route according to the drawn inspection area, so that the unmanned aerial vehicle autonomously and safely inspects a bridge.

The invention provides a panoramic image three-dimensional reconstruction method based on 3DGS, and relates to the technical field of computer vision and image processing, and the method comprises the steps: 1, collecting a panoramic image sequence of a to-be-reconstructed scene, carrying out the unified coding through equidistant cylindrical projection, and obtaining a coding data set; and step 2, executing panoramic motion recovery structure processing on the coded data set, and generating six-degree-of-freedom camera pose parameters of each image and a corresponding sparse three-dimensional point cloud. According to the invention, high-precision and high-efficiency panoramic scene three-dimensional reconstruction is realized, a high-quality panoramic image or a dense three-dimensional model can be output, and the three-dimensional reconstruction quality and efficiency are improved.

The invention relates to the technical field of computers, in particular to a multi-mode-based three-dimensional model editing method and device, equipment and a medium. The method comprises the following steps: acquiring a multi-modal fusion image personalized generation method and a source three-dimensional model; obtaining a personalized image generation network corresponding to the source three-dimensional model, and training the personalized image generation network; based on the reference image list and the corresponding text description, multi-modal embedded information is obtained after fusion; taking the trained personalized image generation network as a skeleton, and adding a multi-personalized learning module to obtain a multi-personalized image editing network; and editing the source three-dimensional scene image according to the multi-modal embedded information by using a multi-personalized image editing network to obtain a single-view-angle edited image. The multi-mode embedded information generated by the method allows a user to input prompt information of multiple modes such as texts, images, sketches and the like, complementarity of prompt of each mode is mined, so that controllability of editing is improved, and high-quality three-dimensional model editing is realized.

The invention discloses a subgrade graded filling construction settlement prediction method and system, and relates to the technical field of subgrade construction.The subgrade graded filling construction settlement prediction system comprises a data sensing module, an edge calculation module, a central processor, an emergency decision module and a digital twinborn platform; non-linear working condition classification is carried out through an edge calculation module, complex working conditions are effectively identified, and the accuracy of working condition classification is improved; a mechanism that environmental factors indirectly influence settlement is disclosed through a central processor, the synergistic effect of environmental and geological factors is captured, then a hybrid prediction model is established to achieve quantitative evaluation of the roadbed filling state, and the adaptability to complex working conditions is improved; and then dynamic balance of settlement control and resource allocation is realized through an emergency decision module, visual support is provided for construction management through digital twinning and 3D modeling, decision efficiency and transparency are improved, and the method has important engineering application value and technical leading.

The invention discloses a fruit appearance defect real-time online detection method and system, and relates to the technical field of image processing, and the system comprises an image capture module, a feature extraction and analysis module, a 3D reconstruction module, a dynamic segmentation module, a defect quantification and grading module, and a topology analysis and detection module. According to the real-time online detection method and system for the fruit appearance defects, the defects of a traditional method in the aspects of detection precision, classification fineness and environmental adaptability are overcome by combining a plurality of processes of multispectral image capture, hierarchical feature extraction, high-dimensional clustering analysis, 3D modeling, defect quantitative evaluation and the like. The system can accurately identify various defect types on the surface of the fruit in real time in a complex detection environment and quantify the severity of the defect types. Compared with the prior art, the system has the advantages that the accuracy, the stability and the real-time performance of defect detection are remarkably improved, an intelligent solution is provided for automatic sorting and quality control of fruits, and meanwhile, the labor cost is reduced.

The invention discloses a virtuality and reality combined display system of a universe museum, and relates to the field of universe technology and museum display technology, the system comprises a data acquisition module, a data analysis and user portrait module, a personalized guide planning module, a virtuality and reality combined display module and a feedback and optimization module; according to the system, user information and cultural relic data are comprehensively and meticulously collected through the data acquisition module, a basis is provided for subsequent personalized display and guide planning, and the data analysis and user portrait module digs potential demands and interests of users, so that displayed contents can accurately match preferences of the users, and the user experience is improved. The virtual-reality combined display module constructs a virtual cultural relic model by using a 3D modeling and rendering technology, realizes seamless joint with an entity exhibit through an AR technology, brings immersive visiting experience to the user, and in addition, due to the existence of the feedback and optimization module, the system can continuously collect user feedback, so that the user experience is improved. And display contents and functions are continuously optimized and perfected.

The invention discloses a visual and three-dimensional modeling luggage automatic identification method, equipment, a medium and a product. The method comprises the following steps: firstly, carrying out dynamic multi-view scanning on luggage entering a scanning area of a conveyor belt to obtain a multi-view image, carrying out deep learning to obtain three-dimensional point cloud data, and fusing the three-dimensional point cloud data with X-ray transmission density data to form a preliminary three-dimensional model; whether the model is complete or not is judged by combining geometric closure and material density continuity, and if not, features are extracted through an adversarial generative network, and occlusion area point cloud data are predicted for complementation; and finally, matching the complementation model features with a dangerous goods feature library, and judging whether the dangerous goods are dangerous goods or not. By implementing the technical scheme provided by the invention, the information of the articles in the luggage can be comprehensively obtained, the complete and accurate three-dimensional model can be constructed, whether the articles are dangerous articles or not can be efficiently and accurately judged, and the efficiency and the safety of aviation security inspection are improved.

The invention relates to the technical field of digital twinning simulation, and discloses a digital twinning-based intelligent simulation system for a lyocell fiber production line, and the system comprises a 3D modeling and digital twinning module which constructs a three-dimensional model of the lyocell fiber production line, associates the three-dimensional model with real-time production data, and finally forms a three-dimensional digital twinning model of the production line; the key equipment state prediction module predicts the residual life of the film evaporator according to the vibration data of the film evaporator; the energy consumption prediction module is used for obtaining key parameters of the glue making process and predicting an energy consumption value according to the process list of the lyocell fiber glue making process; the early warning module is used for early warning in an equipment model corresponding to the target film evaporator in the three-dimensional digital twin model according to the residual life prediction result; and the process management module is responsible for compiling, managing and issuing process files. According to the system disclosed by the invention, all the functional modules are fused and combined together to form a complete system, so that the system is of great significance in guiding lyocell production and can help enterprises to carry out better cost control.

The invention discloses a dynamic three-dimensional reconstruction method based on incremental updating, which belongs to the field of image data processing, and comprises the following steps: acquiring a forestry scene multi-view image to be reconstructed to form an initial data set D0; constructing an initial three-dimensional scene model of the forestry scene based on D0 and 3DGS methods; monitoring a forestry scene to construct an incremental data set Dt of the tth change; during each incremental learning, the previous incremental model is divided into a change area and a non-change area, and the incremental model of the tth incremental learning is obtained by optimizing the change area and the non-change area and constructing a new scene model and is used for image rendering. According to the method, full-scene reconstruction is avoided, and the accuracy of the three-dimensional model can be ensured while the efficiency of three-dimensional reconstruction in a dynamic environment is remarkably improved. And the scene can be updated only by adding a small number of view angle images, so that the cost and time of data acquisition are greatly reduced, and the method is particularly suitable for large-scale monitoring of forestry and the like and scenes needing long-term monitoring and real-time updating.

The invention provides a liver focus three-dimensional modeling method, and belongs to the technical field of image processing based on computer vision. Firstly, a multi-view spatial registration method based on optical flow optimization is designed, pixel-level displacement information of different view images is estimated by calculating an optical flow field, accurate image alignment is achieved, and spatial consistency of three-dimensional reconstruction is improved. And secondly, a three-dimensional reconstruction strategy based on two-dimensional focus segmentation is proposed, the two-dimensional focus segmentation is completed by adopting a lightweight U-Net variant, and a segmentation result is mapped to a three-dimensional space through a voxel probability projection method, so that 3D focus reconstruction is realized, and the calculation cost is reduced. And finally, extracting high-frequency features of the three-dimensional model by adopting a local edge enhancement method based on a Laplacian operator, and strengthening a focus boundary and a key anatomical structure through interpolation optimization, so that the three-dimensional model is more accurate and clearer. Compared with a traditional method, the method has the advantages that the mode of purely depending on image superposition is avoided, and the accuracy of three-dimensional modeling is improved.

The invention discloses a simulation optimization method for a digital twin factory. The simulation optimization method comprises the steps of obtaining workshop equipment data and performing classified storage; generating a task priority and resource configuration rule based on the basic operation data of the equipment; constructing a three-dimensional space model by using a 3D modeling tool, and creating a digital twinborn simulation factory model in combination with real-time production data; constructing a dynamic planning state space and a decision variable, and determining the resource use time, the resource allocation position and the specific quantity of each task; according to the resource allocation scheme and the task chain dependency relationship, evaluating a risk value of a task node in combination with historical equipment fault data; and based on the influence range report of the production fault chain, evaluating a task execution sequence and adjusting resource allocation and task time arrangement. According to the method, the influence of faults on a production plan and resource waste are reduced, the stability and adaptability of a factory system are remarkably enhanced, and the reliability and fine management level of overall production are improved.

The invention provides a production operation dynamic supervision method, which comprises the following key steps: S1, data integration: widely collecting data of different production links, transmitting the data to a database through a network interface, and constructing a comprehensive data basis; s2, establishing a visual monitoring platform to integrate data to drive development, vividly displaying a production state by means of a three-dimensional model, a chart and a report, and helping a manager to intuitively insight; s3, intelligent analysis and early warning: deeply mining a data rule trend by using big data and an artificial intelligence algorithm, accurately setting an early warning threshold value, and giving an alarm in time when the threshold value is exceeded, so as to effectively prevent risks; and S4, collaborative management and decision support are carried out, department information barriers are broken, efficient sharing and collaboration are realized, scientific decision support is provided for managers, and production plans, maintenance strategies and emergency plans are optimized. According to the method, through multi-link collaborative operation, the production operation dynamic management and control capability is comprehensively enhanced, and efficient, safe and robust development of enterprises is powerfully promoted.

The invention provides a high-precision topographic mapping and three-dimensional modeling system based on an unmanned aerial vehicle, and the system comprises an unmanned aerial vehicle cooperation module which is used for deploying a multi-source sensor and a sensor electronic interface on the unmanned aerial vehicle, and building a distributed network of the unmanned aerial vehicle; the real-time dynamic positioning module is used for acquiring unmanned aerial vehicle positioning data and an initial target terrain map; the autonomous control module is used for generating a flight path, performing dynamic adjustment, constructing an autonomous flight control model and outputting a flight control instruction; the data quality enhancement module is used for performing parameter adjustment on the real-time data and performing space and signal level combined processing on the real-time data so as to enhance the data quality; and the terrain model optimization module is used for processing the laser radar point cloud data so as to construct a three-dimensional terrain model post-processing module, and carrying out data visual display and flight suggestion generation. According to the method, the positioning and modeling precision is greatly improved, efficient surveying and mapping are achieved, the single-point fault risk is reduced, and it is guaranteed that tasks can be completed in a high-safety, high-precision and intelligent mode.

The invention discloses a 3D printing path planning method based on electric arc additive anisotropy and a stress field, and the method comprises the steps: constructing a CAD three-dimensional model of a part, and obtaining the stress field of the part through finite element simulation; determining a slice plane; mapping the stress field to a slice plane to form a force flow line; according to the obtained force flow line, rotation transformation regeneration is carried out according to the anisotropy of the used electric arc additive, and a reference trajectory considering the anisotropy of the material is obtained; under the principle of alternate arc starting and extinguishing, the corresponding printing sequence in the layers and between the layers is further planned, and the reference trajectory lines are connected end to end to be planned into a continuous path; and generating a code file, and printing according to the printing sequence. The comprehensive mechanical property of a printed piece is improved.

The invention discloses a CAD automatic modeling method and system based on parameter driving. The method comprises the steps that model parameter information needing modeling is obtained; generating a CAD (Computer Aided Design) model on the basis of parameter analysis, geometric construction and surface recognition schemes; performing reverse reconstruction of the three-dimensional CAD model based on topology analysis, geometric feature extraction, pattern recognition and parameter relation inference; modeling, optimization and feedback evolution are carried out based on model analysis, feature learning and generation of parametric modeling rules; and according to the obtained data information, CAD automatic modeling based on parameter driving is completed. According to the method, CAD automatic modeling based on parameter driving is achieved, the reliability is higher, the accuracy is better, and the efficiency is higher.

An image processing system is configured to receive a three-dimensional (3D) model and a text prompt that describes a scene corresponding to the 3D model. The system may then generate a depth map of the 3D model and generate an output image based on the depth map and the text prompt. The output image may depicts a view of the scene that includes textures described by the text prompt. The output image may be generated using an image generation model.

The invention provides a 3D modeling method based on a digital twin city, and belongs to the technical field of 3D city modeling. Through a multi-source semantic data fusion acquisition means, space-time semantic tags are added to various types of data, the problem of multi-source data isomerism is solved, and semantic unification and efficient fusion of different types of data are realized; by means of hierarchical dynamic modeling means, a building component network is constructed based on triple association of geometry, functions and semantics, so that a model structure better conforms to the logic of the building industry, and the reasonability and efficiency of modeling are improved; a virtual-real two-way mapping means is applied, incremental updating of the model is triggered through a cross-modal semantic comparison algorithm, limitation of traditional static modeling is broken through, and dynamic synchronization of the virtual model and the physical world is achieved; an intelligent optimization means is adopted, a multi-constraint-condition generative adversarial network is combined with a visual attention mechanism, it is ensured that generated textures conform to building geometric features and material specifications, and meanwhile intelligent distribution of rendering resources is achieved.

The invention provides a virtual fitting method based on a color three-dimensional model, and the method comprises the steps: obtaining the body point cloud data of a user through a three-dimensional scanning device, constructing a color three-dimensional human body model, and setting skeleton binding parameters; dividing a pressure sensitive area based on model surface curvature distribution, and generating a dynamic pressure map; performing cloth physical simulation on the model in a physical engine, and extracting deformation response data of the top points of the clothing grids; real-time motion posture data of a user is collected through an inertial sensor, motion distortion correction is conducted, and a joint motion track is generated. Dynamically comparing the joint movement track with the deformation response data to generate a clothing fitting degree deviation report; and optimizing the clothing pattern parameters and the fabric physical attributes based on the deviation report, and outputting a clothing adaptation proposal. According to the invention, the suitability and comfort of clothes can be improved, and the production efficiency and the product quality are improved.

The invention discloses a multi-laser multi-material laser cladding 3D printing method and system, and relates to the technical field of 3D printing, and the method comprises the steps that according to a three-dimensional model of a target component, a printing path and a lap joint point position are determined; carrying out regional division on the working face; a sensor is used for detecting the thickness of each layer in real time, and the printing speed and the laser power are adjusted according to detection data; laser welding is carried out on a lap joint area between the printing layers, and laser annealing is carried out to release residual stress; and according to component requirements, different materials are dynamically switched in the printing process. The multi-printing-head and multi-laser-device cooperative work, path optimization and dynamic feedback control, material dynamic switching and laser annealing treatment technologies are adopted, and the problems of size limitation, insufficient interlayer binding force, complex material switching, path conflict and thermal stress in the large forming part manufacturing process are fundamentally solved. Compared with a traditional process, the printing efficiency, the finished product quality and the production flexibility are remarkably improved.