271 results about "Texture mapping" patented technology

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 discloses an urban building three-dimensional automatic modeling and visualization method, and belongs to the technical field of building three-dimensional modeling. The method comprises the steps that point cloud data, high-resolution images and geographic information system data of urban buildings are acquired, data cleaning, registration and alignment are carried out, and preliminary building digital representation is formed; accurately segmenting each building, and identifying the contour and main structural features of the building; based on the data integrity and the building complexity, adaptively selecting a proper reconstruction strategy to carry out three-dimensional reconstruction; in the reconstruction process, the geometric structure is analyzed and optimized in real time, and potential topological problems are repaired; automatically generating missing details based on a predefined architectural style library and a component library, and performing material inference and texture mapping; a graph structure is used for representing the relation between the buildings, and the positions and orientations of the buildings are adjusted through a global optimization algorithm; a rendering engine supporting multi-level detail switching is developed, and smooth visualization and interaction of a large-scale city scene are achieved.

The invention relates to the field of commodity visualization, in particular to a commodity display interaction visualization method and device. The method comprises the following steps: collecting a multi-azimuth image of a commodity, carrying out three-dimensional texture modeling, and constructing a three-dimensional texture mapping model; performing material light rendering on the three-dimensional texture mapping model to generate a material rendering result; collecting an environment detection image of a commodity display environment, and performing environment illumination adaptation compensation on a material rendering result to obtain an illumination compensation rendering commodity; carrying out attribute information visual layout on the illumination compensation rendering commodity to obtain a commodity visual space; and carrying out interaction response animation analysis according to the commodity visualization space, carrying out multi-target parallel rendering, and executing commodity interaction visualization operation. The form and surface details of the commodity in the real world are accurately restored, the visual reality sense is improved, and the interactive experience feeling of browsing the commodity by a user is enhanced.

The invention discloses a bronze ware ornamentation and pattern digital restoration method based on an image enhancement technology, and relates to the technical field of image restoration, and the method comprises the steps: building a space mapping matrix; extracting multi-modal data features by using the surface state of the topological insulator, and registering a joint data volume; forming a super-resolution image through super-resolution reconstruction; obtaining a material degradation coefficient by using a wavelet finite element method and a graph neural network; generating an adversarial network by utilizing physical constraints, and generating an embarrassment repairing result; a material sensing three-dimensional model is constructed by adopting a wavelet packet decomposition and neural radiation field fusion technology, texture mapping is dynamically adjusted based on a graphene Moire effect, and virtual-real fusion is performed through holographic waveguide AR; by combining advanced technologies such as a metamaterial lens, micro-distance laser scanning, a topological insulator film, a graphene heterojunction and a nerve radiation field, high-precision three-dimensional digital restoration and repair of bronze cultural relics are realized, and immersive augmented reality display experience is provided.

The invention discloses a tunnel fracture recognition method based on three-dimensional live-action reconstruction and ordered re-acquisition of a virtual camera. The method specifically comprises the following steps: acquiring a multi-view rock fracture image; acquiring three-dimensional point cloud data of a tunnel wall surface according to the acquired rock mass fracture image, reconstructing a geometrical shape of the tunnel, mapping acquired texture information to a three-dimensional grid vertex through an image processing algorithm, and generating a three-dimensional tunnel model; setting parameters of the virtual camera, orderly collecting to form a virtual image, and enabling the position of the virtual camera to correspond to the real position of the model; and extracting information of the crack of the virtual image, and projecting the coordinates of the two-dimensional image back to the three-dimensional space through the projection matrix to obtain the space coordinates of the crack. A virtual image is generated by combining a texture mapping technology of a three-dimensional model, so that the limitation of a visual angle, illumination and space in actual image acquisition is overcome, and high-precision identification of tunnel cracks is realized.

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 invention relates to the technical field of computer vision and virtual reality, and discloses a three-dimensional video fusion method based on camera self-calibration and projection texture mapping, and the method comprises the following steps: S1, obtaining video data, and collecting at least one frame of two-dimensional image in a to-be-fused video stream; optionally, the two-dimensional image is preprocessed; and S2, calibrating internal reference of the camera, detecting linear features in the two-dimensional image by using an image processing algorithm, estimating the position of a vanishing point by using a least square method or other optimization algorithms based on the detected linear segment, and calculating an internal reference matrix of the virtual camera according to the optimized vanishing point position. The perspective relation between the video image and the surface of the three-dimensional model is determined through the vanishing point detection technology, accurate fusion of the video image and the three-dimensional model is achieved, the sense of reality of a virtual scene is improved, and the tedious camera calibration process and the complex three-dimensional reconstruction process based on a calibration plate are avoided.

The invention relates to the technical field of three-dimensional scanning, and discloses a binocular three-dimensional scanning system and method with a texture mapping function. The system comprises a depth data acquisition module, a depth data correction module, a point cloud topology construction module, a texture mapping engine module and a mapping optimization module. The depth data acquisition module synchronously acquires a left view and a right view of a target object through a binocular camera array, and generates an original depth image data set; the depth data correction module performs abnormal value detection on the original depth data, extracts discrete distribution through aggregation boundary analysis and replaces abnormal values; the point cloud topology construction module generates a three-dimensional point cloud spatial topology structure, and associates point cloud coordinates with left view pixel positions; the texture mapping engine module projects left view RGB data to the point cloud to generate an initial texture map; and the mapping optimization module verifies the local color consistency through the generative adversarial network, and outputs an optimized three-dimensional texture model. The system improves the texture precision and authenticity of the three-dimensional model.

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 discloses an adversarial texture generation method and system applied to a depth estimation model. The method comprises the following steps: generating an initial adversarial texture pattern based on a potential vector driving pattern generator; performing up-sampling processing on the initial confrontation texture pattern to obtain an up-sampling texture pattern; mapping the up-sampling texture pattern to a specified area of the object model, and performing image rendering on the mapped object model M by using a rendering engine to generate an object image; performing background synthesis on the object image to generate a complete scene attack image; inputting the complete scene attack image into the depth estimation model to obtain the predicted depth of the image at the current view angle; and designing a loss function for optimization based on the predicted depth and the reference depth. According to the scheme, based on the potential vector driven generator, texture mapping and background synthesis processing, the method is not limited to a two-dimensional image task any more, the training efficiency is improved, and the diversity and stability of generated textures are improved.

The invention relates to the technical field of digital twinning, particularly provides a digital twinning construction method based on multi-source point cloud data fusion, and solves the problems of low multi-source point cloud data fusion precision, low calculation efficiency and poor adaptability to complex scenes in the prior art. The method comprises the following steps: S1, preprocessing multi-source point cloud data: carrying out data denoising and coordinate unified processing on the point cloud data of each source; s2, designing a point cloud data fusion algorithm: performing feature extraction and description, feature matching and fusion decision and weighted fusion calculation on the preprocessed point cloud data to obtain fused point cloud data; s3, constructing and optimizing a digital twinborn model: performing triangular mesh generation, model optimization processing, texture mapping and attribute addition on the fused point cloud data, and constructing the digital twinborn model; the digital twinning construction method based on multi-source point cloud data fusion can effectively solve the problems that multi-source point cloud data fusion is low in precision, low in calculation efficiency and poor in adaptability to complex scenes.

The invention relates to the technical field of mining area emergency management, and discloses a mining area three-dimensional visual emergency management system which comprises a data acquisition module and a three-dimensional sand table generation module. The data acquisition module is used for acquiring dynamic data including geological structures (including static exploration and dynamic sensor data), disaster hidden dangers and environmental monitoring; the three-dimensional sand table generation module processes data through a three-dimensional visualization engine, the data preprocessing unit completes unification of a space coordinate system, missing data complementation and abnormal value correction, and the scene rendering unit generates a three-dimensional dynamic sand table through texture mapping, spatial feature fusion, spatial coupling modeling and three-dimensional scene synthesis. The system is provided with functional modules of offline data loading, disaster diffusion simulation, escape route planning and the like, and supports cross-platform rendering and user interaction operation. According to the invention, three-dimensional dynamic display and emergency analysis of mining area multi-source data are realized, and the accuracy and timeliness of disaster early warning and emergency decision making are improved.

The invention belongs to the technical field of augmented reality, and discloses an AR scenario furniture identification and dynamic removal system based on artificial intelligence, and the system comprises the steps: carrying out the multi-view image registration, furniture entity segmentation and shielding completion analysis based on the obtained hotel scene AR image sequence data, and forming a complete furniture contour feature; the style similarity of the furniture multi-dimensional feature vectors is analyzed, and a furniture style recognition result is obtained; the method comprises the following steps: acquiring AR scanning data of a home environment, performing furniture removal priority ranking through space conflict analysis and style coordination evaluation, generating a dynamic removal strategy, establishing furniture three-dimensional model data based on the dynamic removal strategy, and performing material texture mapping and shadow fusion to obtain a realistic rendering effect; an interactive optimization adjustment scheme is generated, and scene parameter real-time adjustment and optimization and visual effect improvement are realized through user feedback; the reality sense of virtual home display and the user experience effect are remarkably improved.

The invention provides a texture mapping method, a texture mapping device, a computer storage medium and electronic equipment, and relates to the technical field of computer graphic processing. The method comprises the following steps: acquiring a world space coordinate and a world space normal of a vertex of a target model; performing texture projection on the world space coordinates on a plurality of world coordinate axes to obtain target texture coordinates of the vertexes of the target model on the world coordinate axes; determining a texture weight value based on the included angles between the world space normal and the plurality of world coordinate axes; and carrying out texture sampling according to the target texture coordinate to obtain an initial map sampling result, and carrying out mixed sampling on the initial map sampling result and the texture weight value on the corresponding world coordinate axis to carry out texture mapping on the to-be-processed model based on the target map sampling result. The method can get rid of dependence on a model topological structure and UV expansion of a three-dimensional model, and realizes a more real, natural, accurate and flexible texture fitting effect without deformation stretching.

The invention discloses an image acquisition method based on three-dimensional modeling, and the method comprises the steps: A, improving the modeling robustness of a complex scene through the integration of a multi-modal sensor, including a visible light camera, a laser radar, an infrared sensor and a six-axis IMU, through the fusion of a data level, a feature level and a decision level; b, evaluating scene complexity in real time by using a convolutional neural network, dynamically adjusting parameters of resolution, frame rate, exposure time and equipment path, and realizing AI adaptive acquisition; c, geometric point cloud modeling and multi-view texture mapping are combined, global model precision is adjusted and optimized through a bundle method, and a hybrid modeling framework is formed. By combining the multi-modal data fusion technology and the artificial intelligence self-adaptive acquisition mechanism, the precision and efficiency in the three-dimensional modeling process are greatly improved, meanwhile, the adaptability of the model to different scenes is remarkably enhanced, the dependence on complex environmental conditions is effectively reduced, and the three-dimensional modeling technology is more flexible and reliable.

The invention discloses a construction site three-dimensional modeling method based on multi-sensor fusion. The method comprises the following steps: synchronously acquiring data by using a laser radar, a camera, an infrared sensor, a GPS (Global Positioning System) and an IMU (Inertial Measurement Unit); the method comprises the following steps of: performing denoising and filtering operation on collected original data, aligning a timestamp and a space of the collected data, fusing the collected multi-source data, and aligning and fusing the processed multi-source point cloud data through a point cloud registration and fusion algorithm to generate a complete three-dimensional point cloud model; generating a grid model by using a surface reconstruction algorithm based on the point cloud data, and performing texture mapping in combination with texture information collected by a camera; the model is simplified and the precision of the model is improved through a model optimization technology, and a reliable three-dimensional visualization foundation for construction management and analysis is formed; real-time detection and modeling of dynamic targets such as mobile equipment and workers on a construction site are realized, and the real-time response capability of the system in a complex construction site environment is ensured through combination of a lightweight neural network architecture and an edge computing technology.

The invention discloses a mining area information three-dimensional perspective model construction method and device, equipment, equipment and a medium, and relates to the technical field of modeling. The method comprises the steps of performing data fusion and voxel filling on multi-source mining area geological data, constructing an initial model according to the data fusion and voxel filling, and performing topological structure optimization; performing surface topology and texture mapping on the model based on a mining area remote sensing image to obtain mining area ground feature distribution transmission data and superposing the data into the model; performing density distribution and density mutation recognition on the model according to the gravity exploration data of the mining area to obtain density distribution transmission data of the mining area, and superposing the density distribution transmission data into the model; resource prediction is carried out based on mining area ground feature / density distribution transmission data; threshold screening is carried out on the topological optimization model based on the prediction result, and then the topological optimization model is superposed into the model; performing deep source focusing processing on the mining area resource area data to obtain deep source focusing area data, and superposing the deep source focusing area data into the model; and carrying out resource visualization on the model to obtain a mining area information three-dimensional perspective model. According to the invention, multi-dimensional fine expression of mining area information can be realized.

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.

The invention discloses a scene electromagnetic texture mapping method and system based on an autonomous mobile robot. The method comprises robot operation and development, radar sensor operation and DART implementation. The robot carries out data acquisition through a sensor and carries out data fusion and processing on the acquired information; the radar sensor operates to detect the surrounding environment through a signal transceiving mechanism, and the obtained signals are fused and processed; in the DART implementation step, visual results of different angles are provided through a visual angle synthesis technology and are finally output in a multi-visual-angle mode. Through a strong coupling mechanism of robot body motion control and radar scanning parameters, a personal error source is eliminated, high-precision motion control is realized based on a robot-radar cooperative control architecture, and based on a DART-NeRF hybrid modeling engine and a lightweight network architecture, model parameters are compressed through adaptive coding, and training and reasoning processes are accelerated.

The invention discloses a planet generation method and system based on spherical display equipment. The method comprises the following steps: acquiring a planet material to be projected; based on preset UV coordinate mapping data, performing spherical projection on the planet material to generate a planet with two poles based on vertical projection and an equator based on cylindrical projection; the acquisition mode of the UV coordinate mapping data specifically comprises the following steps: generating a corresponding cylindrical projection through a cylindrical projection algorithm based on the auxiliary texture; corresponding spherical coordinates are obtained based on auxiliary texture mapping; converting the obtained spherical coordinates into 3D rectangular coordinates; the obtained 3D rectangular coordinates are mapped back to the 2D texture space again, and corresponding vertical projections are generated; determining an equator mask; and generating corresponding UV coordinate mapping data based on the equatorial mask, the cylindrical projection and the vertical projection. According to the invention, through the design of the UV coordinate mapping data, in the process of carrying out spherical projection on the planet material, the resource consumption is reduced, and the dynamic projection precision can be improved at the same time.

The invention belongs to the technical field of building single or multi-view-angle to 3D modeling reconstruction, and provides a 3D reconstruction method based on a real estate building cluster point cloud to MESH neural network. Comprising the steps of original point cloud data acquisition, noise removal, grid filtering, normal vector optimization, density uniformity processing, continuous multilayer 3D convolutional neural network processing, color mapping, texture mapping, color consistency optimization and texture distortion optimization. Through uniform sampling, noise removal and grid filtering, the point cloud data volume is reduced, and the quality of the point cloud data is improved; through the continuous multi-layer 3D convolutional neural network, the local geometric pattern of the building is automatically learned from the data and the features of the building are extracted layer by layer, so that the precision of the three-dimensional grid model is improved; through color consistency optimization and texture distortion optimization, the color and texture mapping effect is optimized, and refined reconstruction of the building is realized.

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 discloses an unmanned aerial vehicle video live-action map generation method and device, a medium and equipment, and belongs to the field of map generation. According to the method, the real-time video data and the pose information of the multiple unmanned aerial vehicles are acquired, projection conversion is carried out, the pose estimation is carried out by utilizing the visual SLAM algorithm and combining the converted pose information, and the camera pose matrix is constructed. And further, processing the video data by adopting a preset densification and orthorectification method in combination with the camera attitude matrix to obtain each video frame. A video frame is divided into a non-overlapping area and an overlapping area, the non-overlapping area is directly integrated to a global map, the overlapping area is divided into sub-maps, overlapping information is processed and then integrated to the global map, and finally a panoramic base map is formed. And finally, integrating the panoramic base map with the 3D GIS through a projection texture mapping technology, and generating an unmanned aerial vehicle video live-action map. The problem that the video live-action map of the unmanned aerial vehicle cannot be accurately and efficiently generated in the prior art is effectively solved.

The invention provides a terrain and ground feature construction system and method based on satellite remote sensing and unmanned aerial vehicle aerial photography, and the method comprises the steps: screening an aerial photography region from a target region according to a ground feature classification initial image of the target region, and carrying out the multi-view dense matching of a multi-view aerial photography image sequence of the aerial photography region, generating a three-dimensional grid model and a second digital surface model of the aerial photography area; performing feature fusion on the first digital surface model and the second digital surface model based on registration constraints of a terrain surface of a target area, and constructing a multi-scale digital surface model of the target area; and performing texture mapping integration on the three-dimensional grid model and the multi-scale digital surface model, outputting a multi-level real scene three-dimensional model of the target area, and completing terrain and ground feature integrated construction of the target area. On the basis of the scheme, advantage complementation of satellite wide-area perception and unmanned aerial vehicle accurate exploration can be realized, so that the integration level of a live-action three-dimensional model in macroscopic coverage and microscopic detail precision can be improved.

Disclosed in the present application are a vehicle-mounted panoramic image generation method, a computer device, a computer storage medium, a computer program product and a mobile platform. The vehicle-mounted panoramic image generation method comprises: acquiring in real time multiple pieces of image data collected by a plurality of cameras; determining point cloud data corresponding to the multiple pieces of image data; on the basis of the point cloud data, correcting a preset three-dimensional model to obtain a corrected three-dimensional model; on the basis of the multiple pieces of image data, performing texture mapping on the corrected three-dimensional model to obtain a dynamic real-scene model; and on the basis of vehicle information and the dynamic real-scene model, generating a vehicle-mounted panoramic image. In the present application, point cloud data corresponding to multiple pieces of image data acquired in real time is used, a preset three-dimensional model is corrected on the basis of the point cloud data, and the corrected three-dimensional model is used to perform texture mapping to obtain a dynamic real-scene model, thereby solving the problem in the prior art whereby ambient objects with height are deformed and stretched due to a mismatch between a preset three-dimensional model and object shapes.

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 relates to the technical field of EMB brake disc visual inspection, and discloses an EMB brake disc defect detection method and system based on visual inspection, and the method comprises the steps: obtaining a complete image set containing a plurality of visual angles, and carrying out the space alignment and feature extraction, and obtaining a surface feature data set; performing interpolation complementation on the surface feature data set, and performing defect detection and space construction on the complemented data set to obtain a space information model; according to the spatial information model, generating point cloud data of the surface of the brake disc, and performing grid optimization to obtain an optimized point cloud grid data set; performing texture mapping and defect analysis on the optimized point cloud grid data set to obtain defect position data; according to the defect position data and the three-dimensional distribution view, depth information of the defect area is extracted, and defect form description data is obtained. According to the method, the multi-angle defect detection precision of the complex curved surface can be improved, so that the surface defects of the brake disc can be comprehensively and accurately detected at multiple angles and multiple dimensions.

The invention 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, and realizing global optimization through a curvature-driven quantum annealing algorithm; designing a contact coefficient online correction mechanism and a multistage fault-tolerant protocol, and establishing differential homeomorphic mapping from a quantum optimization result to an execution instruction; manifold adaptive wavelet transform is adopted to extract optimization features, and a pulse shaping control quantity is generated in combination with deep reinforcement learning. According to the method, traditional optimization local extreme value limitation is broken through, self-adaptive control under material characteristic drift is achieved, the problem of control mismatch caused by multi-physics field coupling is solved, and the precision stability and working condition adaptability of complex texture printing are improved.

The invention relates to the technical field of building area three-dimensional model construction, in particular to a three-dimensional model construction method, system and device based on unmanned aerial vehicle surveying and mapping and a medium. The method comprises the following steps: firstly, carrying out pixel-level segmentation on a building area image obtained by an unmanned aerial vehicle to obtain a ground feature category, and carrying out further segmentation in combination with terrain information to obtain a scene unit; then, performing unit internal matching on scene unit point cloud data acquired by each unmanned aerial vehicle, performing inter-unit registration processing in combination with an absolute positioning reference, and performing curved surface reconstruction and boundary fusion to obtain a three-dimensional point cloud model; and finally, obtaining a multi-angle RGB image set of each scene unit, extracting a visible image, eliminating shielding interference, selecting an optimal visual angle image to reduce texture deformation, and finally mapping the texture of the optimal visual angle image to a three-dimensional point cloud model to obtain a three-dimensional model of a surveying and mapping area, which has an accurate geometric structure and high-fidelity visual features, and is suitable for the three-dimensional point cloud model of the surveying and mapping area. And high-precision and real three-dimensional basic data is provided for surveying and mapping visualization, engineering design and the like.