728 results about "Surface reconstruction" patented technology

The invention provides an esophageal squamous carcinoma detection method and system based on combination of multi-modal information fusion and artificial intelligence, and relates to the technical field of detection. And inputting the fusion feature map corresponding to the multi-modal image information into a pre-trained esophageal squamous carcinoma detection model to perform focus area detection and segmentation on the fusion feature map, and based on a detection result, performing benign and malignant classification and staging prediction on a detected focus by using an integrated learning method in combination with a classification algorithm to obtain the esophageal squamous carcinoma. Outputting a classification result and a visual heat map; converting the extracted focus area information into three-dimensional point cloud data by using an improved point cloud reconstruction algorithm; performing space division and noise reduction processing on the three-dimensional point cloud data by adopting a self-adaptive octree structure; and generating a smooth lesion three-dimensional model by using an improved Poisson surface reconstruction algorithm in combination with a curved surface subdivision technology.

The invention relates to the technical field of bridge engineering, in particular to a cable structure bridge design method adopting a BIM (Building Information Modeling) model, which comprises the steps of three-dimensional bridge foundation model construction, cable structure parameterization configuration, nonlinear mechanical simulation, construction error modeling, feedback optimization and the like. Through introduction of structured geological data and NURBS curved surface reconstruction, a geological-structure integrated model is realized. Adopting a genetic algorithm and a particle swarm optimization method to intelligently configure pile foundation and cable parameters; a construction error closed-loop adjustment mechanism is constructed through dynamic simulation and real-time tension feedback control; and finally, parameter correction write-back and BIM delivery model integration is realized. According to the invention, the design precision, the construction stage adaptability and the digital delivery integrity of the cable structure can be improved, and the method is suitable for cable structure bridge engineering with complex geology and high-precision control requirements.

The invention relates to the technical field of coordinate conversion, in particular to a CAD and BIM model coordinate automatic conversion method and system based on coordinate mapping, and the method comprises the following steps: extracting CAD building two-dimensional coordinates input by reference to a building drawing, constructing an initial two-dimensional triangular mesh, extracting key geometric feature points of a building, and combining the floor height parameter and corner information of the building to obtain a CAD and BIM model coordinate automatic conversion model; and mapping the two-dimensional grid to a three-dimensional coordinate space to generate initial building three-dimensional point cloud data. According to the method, a high-quality initial triangular mesh is constructed through a Delaunay triangulation algorithm, coordinate information of a sparse position is accurately captured, a Poisson surface reconstruction technology is combined, global curved surface fitting and smoothing processing are performed on point clouds of a sparse region, and density compensation and precision improvement of coordinate point distribution are realized. According to the optimization mode, the problem of model precision loss is effectively relieved in complex scenes such as building corners, special-shaped spaces and floor height changes.

The invention provides a power transmission line three-dimensional reconstruction method based on an unmanned aerial vehicle and a laser radar, and the method comprises the steps: dynamically adjusting the scanning field angle and scanning frequency of the laser radar according to the flight attitude of the unmanned aerial vehicle and the direction of a cable, obtaining the original point cloud data of the cable at different angles and different densities, carrying out the preprocessing of the obtained original point cloud data, and obtaining a pre-processed point cloud data; obvious noisy points and outliers are removed, and cable point cloud data after preliminary filtering are obtained; and in a local tangent coordinate system, point cloud simplification and curved surface reconstruction are carried out on each local cable point cloud segment to obtain a local cable three-dimensional model, and through coordinate system inverse transformation, the local cable three-dimensional models are spliced into a complete cable three-dimensional model to realize three-dimensional accurate reconstruction of the cable. According to the invention, the problem of accurate three-dimensional reconstruction of a power transmission line in a complex environment is effectively solved, the efficiency and precision of cable detection and maintenance are improved, and during later upgrading and reconstruction or new project construction, electric power personnel can conveniently and rapidly master cable information.

The invention discloses a real-time three-dimensional modeling method and system based on 5G flight control and a medium, and belongs to the field of three-dimensional modeling, and the method comprises the steps: obtaining a modeling demand and task environment parameters of a user, and planning a route; controlling the unmanned aerial vehicle to fly according to the planned route; judging whether the position data and the attitude data of the unmanned aerial vehicle at each waypoint are within a preset threshold range, and if so, controlling the unmanned aerial vehicle to collect image data of the target area; the collected image data is preprocessed; extracting feature point data of the target area by utilizing machine learning according to the preprocessed image data; converting the feature point data of the target area into sparse point clouds by using a triangulation algorithm; converting the sparse point clouds into dense point clouds through an MVS algorithm; and according to the pre-processed dense point cloud, a Poisson surface reconstruction algorithm is adopted to establish a three-dimensional grid model of the target area. Aiming at the low precision of unmanned aerial vehicle three-dimensional modeling in the prior art, the method improves the precision of unmanned aerial vehicle three-dimensional modeling.

The invention relates to the field of medical robots, and discloses a meridian point foundation construction method for precise positioning of an acupuncture robot, which comprises the following steps: scanning skin texture, muscle contour and skeleton mark features of a human body surface, and establishing a human body surface feature digital model; the method comprises the following steps: acquiring temperature distribution data of a human body surface, human body surface feature digital model data and elastic modulus data, performing weight mapping feature level fusion to generate an enhanced acupuncture point feature map, and establishing an acupuncture point-meridian association relationship matrix based on the enhanced acupuncture point feature map; compared with the prior art, the method has the advantages that three-dimensional body surface scanning, infrared thermal imaging and elastic modulus data are integrated through the multi-modal data fusion technology to generate the enhanced acupoint feature map, the dynamic meridian-acupoint twinborn model is constructed in combination with double-ellipse section fitting and implicit curved surface reconstruction, and tissue deformation is simulated in real time.

The invention provides a multi-angle photographing and three-dimensional reconstruction method and system for soft tissue, and relates to the technical field of soft tissue three-dimensional reconstruction, and the method comprises the steps: analyzing soft tissue features based on deep learning, generating a bulb tube motion track and sampling interval data, and controlling a mechanical arm to drive a bulb tube to collect projection images at multiple angles; screening an optimal image sequence by using an image quality evaluation network, and performing preprocessing such as material decomposition, feature extraction, space registration and image optimization; and inputting the optimized image and the material features into a reconstruction model, performing iterative calculation in combination with an anatomical structure template to generate density distribution data, performing curved surface reconstruction and intelligent tissue segmentation based on graph convolution based on the density distribution data, and finally generating a three-dimensional model containing tissue layering information.

The invention relates to the technical field of rock mechanics, and discloses a rock three-dimensional reconstruction method and system based on multi-source information fusion, and the method comprises the steps: obtaining and preprocessing data, carrying out the spatial feature learning of a fusion feature vector through a 3D-CNN network, and constructing a three-dimensional voxel model of rock microscopic damage; converting the fused image data into a point cloud model of the underground cavern surrounding rock structure by adopting a three-dimensional reconstruction algorithm based on point cloud, and constructing a digital twin framework of the underground cavern surrounding rock structure based on an implicit surface reconstruction algorithm; feature parameters output by the three-dimensional voxel model and the digital twinning framework are used as input, and the optimal supporting opportunity and supporting parameters are output through an LSTM-CNN fusion model; in the underground engineering construction process, surrounding rock deformation data are collected in real time, and a supporting scheme is adjusted in real time through a depth deterministic strategy gradient algorithm; according to the method, the scientificity and timeliness of support design under complex geological conditions can be improved.

The invention provides a building measurement method and system based on an intelligent robot, and relates to the technical field of intelligent robots, and the method comprises the steps: deploying the intelligent robot to a to-be-measured building area; determining a final driving path of the intelligent robot according to the layout of the to-be-detected building area; the intelligent robot automatically runs along the final running path, and acquires three-dimensional point cloud data, image information and geographic position information of the building environment by using an internal sensor assembly; and processing the three-dimensional point cloud data, the image information and the geographic position information of the building environment, including point cloud splicing, denoising, registration and surface reconstruction, to generate a three-dimensional model of the building. By automatically collecting and processing data, the building three-dimensional model and the detailed measurement report are efficiently generated, the measurement precision and efficiency are improved, and the labor cost is reduced.

Disclosed in the present invention is a bridge scour curved surface morphological feature reconstruction method based on three-dimensional sonar point clouds, comprising the following steps: collecting point cloud data of a three-dimensional morphology of an underwater riverbed terrain near a bridge foundation, and acquiring original point cloud data of a complete morphology of an underwater riverbed; performing denoising and ball pivoting reconstruction preprocessing on the collected original point cloud data to complete preliminary reconstruction of point clouds; on the basis of the point cloud data having undergone preliminary reconstruction, performing point cloud binarization-based scour morphology recognition on the basis of a computer vision principle, calculating scour pit element classification values of all the point clouds, and recognizing scour pit point clouds; on the basis of the recognized scour pit point clouds, using a K-means clustering algorithm for clustering, and calculating the maximum depth of each pier scour pit; and on the basis of the obtained scour pit element classification values of all the point clouds, providing a curved surface reconstruction method based on scour recognition to perform high-precision curved surface reconstruction on the scour pits. The present invention can achieve high-precision scour pit morphology reconstruction.

The embodiment of the invention provides a scene surface reconstruction method and device, equipment and a medium, and relates to the technical field of computer graphics. The method comprises the following steps of: firstly, introducing an initialized three-dimensional Gaussian model, and determining attribute information and position information of two-dimensional Gaussian corresponding to three-dimensional anchor Gaussian by combining a multi-view image sequence of a target scene; secondly, utilizing the attribute information and the position information to generate a rendered image through a Gaussian splashing method; and then, according to the rendered image and an image with the same view angle as the rendered image in the multi-view image sequence, updating the initialized three-dimensional Gaussian model by minimizing a rendering loss function. And finally, depth information is determined according to the updated three-dimensional Gaussian model and the multi-view image sequence, and a surface model of the target scene is constructed through a three-dimensional reconstruction algorithm according to the depth information and the rendered image, so that the structure and details of the target scene can be reflected more accurately, the floating object phenomenon is avoided, and the accuracy of the target scene is improved. And the quality and the accuracy of scene reconstruction are obviously improved.

The invention provides a part surface efficient three-dimensional reconstruction method based on adaptive octree sampling, and belongs to the field of surface reconstruction. The part surface efficient three-dimensional reconstruction method based on self-adaptive octree sampling comprises the following steps of performing multi-stage filtering and denoising on collected point cloud data; octree nodes are adaptively divided according to local point cloud density and curvature features, the curvature of each node is calculated, feature region marking is carried out, voxel downsampling processing is carried out on non-feature regions, curvature weighted random sampling processing is carried out on feature regions (such as cracks and recesses), and high resolution of the regions is reserved; a multi-resolution space grid is generated based on octree hierarchy, a hierarchical symbol distance field is constructed, and the Poisson surface reconstruction process is accelerated. The method can be used in the fields of surface topography analysis, process optimization, quality control and the like, is particularly suitable for scenes requiring efficient and accurate surface topography detection, and has a wide application prospect.

The invention discloses a generalized neural radiation field reconstruction method based on multi-modal information fusion, and the method specifically comprises the following steps: 1, constructing a luminosity feature body and a geometric feature body based on unstructured multiple views, and constructing a multi-modal neural coding body through progressive complementary fusion; step 2, converting the multi-modal neural coding body and the original RGB pixel body of the unstructured multi-view into volume density and radiation brightness; 3, sampling light rays, and fusing context features of the sampled light rays to obtain context features of the light rays; and step 4, decoding the volume density and the radiation brightness by using the light context features, rendering to generate a free view angle RGB-D image, and then guiding dense reconstruction of a low texture scene by combining photometric supervision and sparse geometric supervision. According to the method, the problem of shape radiation ambiguity can be solved, high-quality three-dimensional reconstruction and two-dimensional rendering are realized, and the surface reconstruction precision of the generalized neural radiation field is improved.

The invention discloses a method for determining a preset position of a video monitoring camera. Camera presetting positions usually need to be manually set one by one, and time and labor are wasted. The method is used for a video monitoring system, and automatic setting of the preset position of the camera is realized by utilizing a group of scene images and the to-be-monitored target image, so that the efficiency is greatly improved. The method comprises the following steps: acquiring feature points based on a scene image set by adopting a computer vision technology, generating a three-dimensional model of a scene by adopting a motion recovery structure technology and a surface reconstruction algorithm, and obtaining the position of a to-be-monitored target in a three-dimensional space by matching the feature points of a to-be-monitored target image with the feature points of the scene image set. Therefore, a proper camera is selected, a corresponding preset position is calculated, and finally the preset position is corrected according to an actual monitoring effect.

The embodiment of the invention relates to the technical field of data modeling analysis, and discloses a tunnel rock stratum large deformation analysis method and system based on three-dimensional modeling, and the method comprises the steps: collecting initial three-dimensional point cloud data through three-dimensional laser scanning; constructing an initial three-dimensional geologic model containing spatial morphological characteristics and a rock stratum interface geometric topological relation through space coordinate matching and curved surface reconstruction; finite element unstructured mesh generation is carried out on the model, and a rock stratum mechanical analysis model is established in combination with physical and mechanical parameters; inputting construction parameters and process information, activating unit nodes in sequence, and solving a force balance equation to simulate stress distribution; identifying a potential deformation area through iterative calculation, and adjusting boundary conditions to predict a deformation trend; the three-dimensional space distribution cloud atlas, the time evolution curve and the position marks are fused to generate multi-view deformation early warning information, the accuracy and the visualization degree of tunnel rock stratum deformation analysis are improved, and support is provided for construction safety.

The invention discloses a storage intelligent monitoring and checking integrated system and method based on multi-technology fusion, and particularly relates to the technical field of storage monitoring, the system obtains environmental parameters and cargo data in real time through a multi-source data acquisition module, carries out cargo identification and segmentation by using YOLOv7 and Mask R-CNN, and carries out storage monitoring and checking on the cargo. A three-dimensional model is constructed in combination with a Poisson surface reconstruction algorithm to calculate volume weight, an environment anomaly analysis module generates an early warning signal through dynamic threshold and influence level evaluation, and an intelligent decision module fuses data to realize quantity anomaly alarm and multi-level response and outputs a three-dimensional visual inventory report. According to the method, the problems of multiple blind areas, low checking efficiency, slow abnormal response and the like of traditional storage monitoring are solved, full coverage of environment monitoring, high accuracy of goods identification, low error of volume calculation and intelligence of abnormal handling are realized, and the automation and digitization levels of storage management are remarkably improved.

The invention relates to a curved surface contour analysis method and related equipment for laser multi-axis linkage machining, and the method comprises the following steps: carrying out the curved surface reconstruction of a target curved surface workpiece based on a three-dimensional point cloud data set, and obtaining a digital curved surface model; performing shape analysis on the digital curved surface model to obtain a curved surface feature descriptor, and if the curved surface feature descriptor does not meet an expected geometric characteristic standard, performing spectral decomposition on the digital curved surface model based on the curved surface feature descriptor to obtain a contour feature spectrum; performing path planning on the contour characteristic spectrum based on a geodesic theory to obtain a processing track sequence; and performing kinematics solution on the processing track sequence to obtain linkage control parameters of each axis, and adjusting the linkage control parameters of each axis based on the expected geometric characteristic standard, thereby solving the technical problem that the processed curved surface workpiece cannot reach the expected geometric characteristic standard due to lack of an effective curved surface contour analysis method.

The invention provides a chip bonding wire three-dimensional measurement method and system based on an inner cavity reflection camera system, and relates to the technical field of three-dimensional measurement. The method comprises the following steps: performing one-time exposure imaging on a chip bonding wire to be detected through an inner cavity reflection camera system to obtain at least three mutually independent visual angle images in the same frame; performing brightness normalization compensation and geometric calibration on the visual angle image to obtain a visual angle data set with uniform brightness and correlation; pairing the view angle data sets in pairs, extracting parallax information by using a feature matching algorithm based on optical flow, and fusing multiple pairs of parallax to generate a lead three-dimensional point cloud; performing noise filtering and curved surface reconstruction on the three-dimensional point cloud to obtain a continuous three-dimensional grid model of a lead; and performing texture mapping on the three-dimensional grid model by adopting any visual angle in the visual angle image or the combination of the visual angles, and outputting a lead three-dimensional reconstruction result with textures. According to the invention, high-precision, large-depth-of-field and rapid three-dimensional measurement of the chip bonding wire is realized.

The invention provides a structure surface multi-disease three-dimensional measurement method and device, equipment and a medium. The method comprises the steps that an image sequence carrying GPS coordinate information is collected; performing depth calculation on the image sequence by using a three-dimensional reconstruction technology, and performing three-dimensional reconstruction on a scene to generate an initial three-dimensional model; carrying out disease determination and point cloud processing to obtain a three-dimensional point cloud model of a specified color and each disease point cloud instance; using a skeleton extraction method and a boundary point extraction algorithm to extract a boundary point set and a skeleton point set of the skeleton point set corresponding to the crack point cloud, and according to each obtained skeleton point set and the corresponding boundary point set, performing quantitative calculation on the length and the width of each crack; generating a spalling surface grid model by using a Poisson surface reconstruction algorithm and a hole filling algorithm, and calculating and determining the volume of the three-dimensional spalling instance according to the spalling surface grid model; and determining the normal direction of each point of the corrosion cloud instance, generating a grid model by using a Poisson surface reconstruction algorithm, and calculating the corrosion area.

The invention discloses a porcelain bushing power transformation equipment surface modeling method based on an unmanned aerial vehicle and light three-dimensional Gaussian, and the method comprises the steps: determining an unmanned aerial vehicle inspection task route, shooting porcelain bushing power transformation equipment through the unmanned aerial vehicle in a multi-view manner, obtaining an equipment image set, carrying out the noise reduction processing of the equipment image set, and carrying out the camera pose estimation. Obtaining surface depth information of the equipment image set based on an SDF function; dense point clouds are generated based on the equipment images and the corresponding camera pose information, three-dimensional Gaussian is constructed according to the dense point clouds, and rendered images are obtained; compressing the three-dimensional Gaussian through a light Gaussian method; establishing a neural implicit surface reconstruction model; constructing a composite loss function, and training and optimizing the reconstruction model based on the composite loss function; according to the method, the lightweight Gaussian compression technology is introduced into the implicit surface reconstruction method, efficient compression and rapid rendering of the scene are achieved, the storage requirement is remarkably reduced, and the modeling precision of the equipment surface and the capturing capacity of complex surface details are improved.

The invention discloses a prediction method for quantifying the development degree of undermining diseases of rammed earth cultural relics, and relates to the field of cultural relic protection. The method comprises the steps of obtaining three-dimensional laser point cloud data and close photography three-dimensional model data of the rammed earth cultural relics; fusion of the three-dimensional laser point cloud model and the close photography three-dimensional model is realized, and a rammed earth cultural relic undermining disease three-dimensional model is constructed; based on the rammed earth cultural relic undermining disease stereoscopic model, quantitative indexes of undermining disease development are extracted, and an undermining disease development prediction model is constructed and optimized; and generating and outputting a quantitative report of the development degree of the undermining disease of the rammed earth cultural relics. According to the method, three-dimensional laser scanning and close photogrammetry are combined, differentiated routes are designed for areas with different heights, alignment of cross section contours of different models is realized based on Fourier description, a Poisson curved surface reconstruction technology is combined with a hole filling algorithm to complement missing parts of the models, spatial distribution and morphological characteristics of undercut diseases are intuitively presented, and the method is suitable for large-scale popularization and application. The change rule of undercut diseases along with time is quantified, and protection work is promoted to be changed from passive repair to active prevention.

The invention provides an intelligent toothbrush based on AI visual identification and an oral health assessment method, and relates to the technical field of artificial intelligence and computer vision. The intelligent toothbrush based on AI visual identification and the oral health assessment method comprise the following steps: S1, based on a built-in multispectral camera of the intelligent toothbrush, dynamically adjusting illumination parameters of different oral regions by adopting a visible light and near-infrared bimodal synchronous acquisition algorithm and through a self-adaptive exposure compensation technology, high-resolution images and transmission data of tooth surfaces and gingival lines are obtained, and a multi-mode oral cavity image data set is generated. Illumination parameters are dynamically adjusted through a multispectral camera to obtain high-resolution bimodal data, the focus detection precision is improved in combination with cross-modal feature fusion, the problem that traditional single-modal imaging is insufficient in early-stage dental caries recognition is solved, and the accuracy of early-stage dental caries recognition is improved based on laser radar point cloud complementation and a three-dimensional surface reconstruction technology. And mapping the two-dimensional focus label into a dynamic three-dimensional plaque distribution model.

The invention relates to the technical field of point cloud processing, and discloses a point cloud data processing method, system and device for industrial three-dimensional model construction. The method comprises the following steps: carrying out denoising and down-sampling processing on original point cloud data of an industrial part to obtain preprocessed point cloud data, calculating a local geometric descriptor, converting the local geometric descriptor into an industrial feature recurrent plot through a recurrent plot algorithm, inputting the recurrent plot into a convolutional neural network to extract a high-dimensional geometric feature vector, and mapping the feature vectors into B-spline curved surface control parameters through a deep belief network, and performing point cloud reconstruction quality evaluation according to the control parameters to obtain geometric accuracy error data and curved surface reconstruction integrity data. According to the method, the problems that in existing industrial three-dimensional model construction, a point cloud data processing method lacks intelligent feature recognition, the reconstruction precision is insufficient, and manufacturing constraints are not fully considered are solved, and the recognition accuracy of geometric features of complex industrial parts and the precision of three-dimensional model reconstruction are improved.

The present invention discloses an in-situ detection device and method for the surface shape of an optical-mechanical component, which belongs to the field of optical precision detection technology, and aims to solve the problem in the prior art that there is a lack of in-situ monitoring and detection of surface shape distortion during the adjustment process of an optical-mechanical component. The laser light generated by the laser in the device is incident on the optical-mechanical component to be measured after passing through a beam isolator, a beam splitter prism, and a collimator A in sequence, and is reflected. The reflected light of the optical-mechanical component to be measured is incident on the beam splitter prism after passing through the collimator A and is reflected. The reflected light of the beam splitter prism is incident on a CCD camera after passing through a perforated light screen, a collimator B, and a phase plate. The CCD camera is connected to a computer system, and the light spot diagram recorded by the CCD camera will be input into the computer system for in-situ detection of the surface shape. The method modulates the reflected light of the sample to be measured by a phase plate, and uses a phase reconstruction algorithm based on light field diffraction iteration to realize sample surface shape reconstruction. It has the advantages of high measurement accuracy, no need for a reference plane, and strong vibration resistance.

According to the movie and television game animation point cloud three-dimensional curved surface reconstruction hole repairing method, an optimized Poisson curved surface reconstruction method is established, noise reduction processing is carried out on wrong point cloud data, abnormal points are removed, if data density is sparse, bicubic spline interpolation is adopted to improve the point cloud density, and the point cloud reconstruction efficiency is improved. Establishing a transfer low-square optimization method to accurately calculate point cloud normal vectors, adjusting the directions of the point cloud normal vectors to be consistent, improving the calculation precision of the normal vectors, and redirecting the normal vectors to ensure the consistency of the point cloud normal vectors; aiming at the fact that holes influencing a data model exist in a triangular mesh model, a triangular mesh optimization, adjustment and repair method based on a radial basis model is adopted, finally, good continuity can be kept between a repair result and a triangular mesh curved surface around the holes, good geometric consistency is kept between a repaired triangular mesh and a triangular mesh on the surface of an original model, and the repair accuracy is improved. The method is high in curved surface reconstruction speed, high in quality and suitable for being applied to multiple industries such as movie and television game cartoons.

The invention provides a blood vessel image processing analysis method and system combining magnetic resonance blood vessel and blood vessel wall imaging, and the system comprises a data obtaining module which obtains a blood vessel enhancement image and a blood vessel wall image; the image registration module is used for registering the blood vessel wall image to the blood vessel enhanced image to obtain a registered blood vessel wall image; the segmentation module is used for obtaining a blood vessel lumen segmentation result and a blood vessel wall segmentation result; the fusion module is used for carrying out weighted fusion on the blood vessel enhanced image and the registered blood vessel wall image to obtain a fused image; the analysis module is used for calculating an intersection region of a blood vessel lumen segmentation result and a blood vessel wall segmentation result; and the three-dimensional visualization and curved surface reconstruction module is used for performing three-dimensional skeleton extraction and curved surface reconstruction on the three-dimensional connected domain of the suspected occluded blood vessel. According to the method, the information of the blood vessel lumen and the blood vessel wall can be obtained at the same time, the defect of a traditional imaging means in evaluating the condition of the blood vessel wall at the far end of the occluded blood vessel is overcome, and the time needed by preoperative evaluation is remarkably shortened through automatic processing and analysis.

The invention discloses a multi-modal measurement system and method of a three-coordinate measuring machine, relates to the cross technical field of precision measurement, computer vision and intelligent manufacturing, and is used for solving the problems of low automation degree, strong subjective dependence and lack of assembly performance prediction capability in automobile covering part characteristic line detection. According to the method, point cloud data and positioning coordinates are synchronously collected through a multi-mode sensor, and a fusion point cloud sequence is generated through time sequence synchronization; constructing a high-precision three-dimensional point cloud model through noise filtering, registration and curved surface reconstruction; automatically extracting a feature line path based on curvature analysis and generating an analysis section; calculating a sharpness index through contour fitting, and generating a quality evaluation coefficient in combination with a CAD ideal model contour tolerance deviation; and finally, defects are identified through virtual assembly analysis, a sensor remeasurement path instruction is generated, and a quality report is output in combination with a quality coefficient, so that the detection precision, the efficiency and the assembly quality prediction capability in the measurement process of the three-coordinate measuring machine are improved.

The invention provides a cuttable interactive software simulation method and system based on a GPU accelerated substance point method, and belongs to the field of computer graphics physical simulation, and the method comprises the steps: S1, carrying out the sampling and initialization of a to-be-simulated three-dimensional software model and a rigid body model interacting with the to-be-simulated three-dimensional software model; s2, based on a virtual scene to be simulated, constructing an initial GPU secondary sparse acceleration structure Ggrid; s3, carrying out expansion on the Ggrid; s4, updating the state of the rigid body model, and constructing a rigid body cutting field of Ggrid; s5, on the basis of the Ggrid and the rigid body cutting field, the physical explicit integral of the three-dimensional software model to be simulated is solved in parallel, and the position of the lagrangian particle at the next moment is obtained; and S6, during the last iteration of each frame, reconstructing a surface triangular mesh of the Lagrange particle cluster in real time based on Ggrid, and smoothing the surface triangular mesh. According to the method disclosed by the invention, multi-material soft deformation, cutting interaction, crushing and real-time surface reconstruction are realized.

The embodiment of the invention discloses a high-precision three-dimensional surface reconstruction method and device based on polarization information enhancement. A specific embodiment of the method comprises the following steps: acquiring multi-view polarization images by using a polarization camera to obtain a polarization image set; performing structured light initialization processing on the target image to generate initialized target image information; inversely projecting the accurate depth information set into a three-dimensional space to obtain enhanced Gaussian point cloud data; gaussian point cloud de-reflection processing is carried out on the initialized target image information to generate de-reflection Gaussian point cloud data; generating Gaussian point cloud data based on the enhanced Gaussian point cloud data and the de-reflected Gaussian point cloud data; and performing data optimization and reconstruction processing on the Gaussian point cloud data to generate a three-dimensional triangular patch. According to the embodiment, the precision and efficiency of three-dimensional surface reconstruction can be improved.

The invention provides an inspection-oriented structure three-dimensional model data optimization method, which comprises the following steps of: analyzing assembly body model data generated by a three-dimensional design platform, and extracting an original data set containing a BREP topological structure, PMI labeling information and a hierarchical relationship; dynamically removing welding nodes, process auxiliary lines and non-geometric attribute data; performing multi-precision curved surface reconstruction on the BREP entity; grid fusion optimization based on material attributes is implemented, triangular patches of the same material are combined, and a vertex index table is reconstructed; constructing a lightweight assembly relation tree, and converting the spatial poses of the parts into a relative coordinate system transformation matrix; generating a lightweight metadata file containing measurable geometric parameters; and outputting a JT format lightweight model which accords with the ISO 14306 standard. According to the technical scheme, on the premise that the model states before and after lightweight processing are consistent, the data size of the model can be reduced, reduction of the overall data size of the three-dimensional model is promoted, and the opening and loading speed of the called model is greatly increased.