1529 results about "Three dimensional imaging" patented technology

The invention relates to the technical field of transformer abnormity monitoring, in particular to a transformer abnormity monitoring method, device and equipment and a storage medium. The method comprises the following steps: acquiring multi-source state parameters of a transformer; carrying out time sequence load change analysis on the multi-source state parameters of the transformer, and carrying out deep correlation mining between features to generate a load-temperature change atlas; performing three-dimensional imaging scanning on the transformer, and marking a transformer assembly; performing center point space positioning calculation on the transformer assembly to obtain a plurality of assembly accurate position coordinates; three-dimensional form point cloud modeling is carried out on the load-temperature change atlas based on the precise position coordinates of the multiple assemblies, dynamic state attribute rendering is carried out, and therefore an operation state twin model is constructed; and performing multi-period state trend prediction on the operation state twin model, performing sequential serialization processing, and constructing a state trend prediction curve. According to the invention, efficient and accurate transformer abnormity monitoring is realized.

The invention discloses a reservoir bank slope geological disaster risk identification method based on an unmanned aerial vehicle laser radar, and relates to the technical field of reservoir bank slope prevention and control, an unmanned aerial vehicle is used for carrying laser radar equipment, flight scanning is carried out on a reservoir bank slope area, and three-dimensional point cloud data is obtained. According to the reservoir bank slope identification method based on the unmanned aerial vehicle laser radar detection data, high-precision terrain and geological information of the reservoir bank slope is rapidly acquired in a non-contact manner by using the three-dimensional imaging capability of the unmanned aerial vehicle laser radar technology, so that the data acquisition efficiency and safety are greatly improved; the method also remarkably improves the precision and integrity of data, accurately captures key topographic factors such as topographic relief, gradient, slope direction and the like through laser radar scanning, and provides a solid foundation for the accurate recognition of bank slope types in combination with geological factors such as geological structures, lithology and the like, so that the prediction and evaluation of bank slope disasters are more accurate. Preventive measures can be taken in advance, and disaster risks are reduced.

The invention belongs to the technical field of three-dimensional imaging and measurement, and particularly discloses a laser scanning three-dimensional imaging method and device, a medium and equipment, and the method comprises the steps: obtaining laser scanning data of a target object, and the laser scanning data comprises depth data including reflection intensity, a scanning angle, a timestamp and flight time; preprocessing the laser scanning data, and fusing a time sequence and scanning path information to obtain multi-channel input features adaptive to a neural network; constructing a three-dimensional geometric reconstruction model, and training the model; inputting the multi-channel input features into a trained three-dimensional geometric reconstruction model to obtain a dual-channel output tensor containing a dense depth map of the target object and a corresponding uncertainty map; converting the dual-channel output tensor comprising the dense depth map of the target object and the corresponding uncertainty map into a three-dimensional point cloud under world coordinates; and post-processing the three-dimensional point cloud to obtain a three-dimensional image of the target object.

The invention relates to the technical field of three-dimensional imaging, and discloses a high-precision underwater structured light three-dimensional point cloud imaging method and system, and the method comprises the following steps: deploying a plurality of sensor nodes, monitoring the temperature, salinity and turbidity key parameters of a water body in real time, selecting proper light source wavelength and power according to the collected data, and carrying out the three-dimensional point cloud imaging of the underwater structured light. It is ensured that the optimal signal-to-noise ratio is obtained under the current condition, and meanwhile the exposure time and gain setting of the camera are initialized. According to the method, the optimal signal-to-noise ratio is obtained by monitoring water body conditions in real time and dynamically adjusting light source characteristics, the optimal structured light pattern is predicted by using a machine learning model, scattering noise is removed, advanced registration and fusion algorithms and an accurate phase unwrapping method are applied, and a high-quality comprehensive structured light pattern is generated. Point cloud gaps are filled through a geometric correction algorithm and an interpolation / filtering algorithm, so that a reconstruction model is closer to the surface of a real object.

The invention relates to a fire prevention and control smart network method and system based on Beidou satellite navigation. The method comprises the following steps: firstly, acquiring real-time operation data of fire-fighting equipment in a building, and scanning a building structure through a three-dimensional imaging device to generate a three-dimensional digital model; secondly, fusing the real-time operation data, the three-dimensional digital model and preset environment parameters to form a fire prevention and control reference data set; thirdly, carrying out multi-dimensional data comparison on the reference data set based on a preset fire-fighting standard program, and generating an alarm signal with spatial positioning information; then, determining a fire-fighting facility failure area according to the alarm signal, and calculating a fire risk diffusion parameter; and finally, generating a grading early warning instruction according to the risk diffusion parameters, and constructing an electronic combat map containing the optimal rescue path. The method provides global and accurate basic data support for fire prevention and control, improves the timeliness and accuracy of early warning, optimizes the rescue path, and improves the fire disposal efficiency.

The present invention discloses a rake-shaped head-end high-precision multipolar mapping electrode catheter, and the technical problem to be solved is to improve the accuracy of the mapping signal, reduce the difficulty of the operation, and improve the efficiency of the operation. The present invention is provided with a catheter, and the distal end of the catheter is provided with 2 to 8 branch tubes with the distal end portions being arranged in parallel in a straight line and the proximal end portions being in an arc shape. The proximal ends of the branch tubes are gradually gathered and connected to the distal ends of the end tubes. At least two ring electrodes are provided on the outer surface of the branch tubes, and the number of ring electrodes of each branch tube is the same. An escort tube is sleeved on the outer surface of the catheter, which forms an intermittent match with the catheter. Compared with the prior art, the present invention can quickly and safely perform high-density mapping in the entire heart cavity of the heart. The escort tube facilitates pushing the branch tube to the distal end, and the sensor can realize the positioning of the catheter. The three-dimensional cardiac electrophysiological mapping of the computer can directly and quickly perform three-dimensional imaging of the patient's heart cavity, and complete three-dimensional modeling, which greatly increases the effectiveness and operability of the operation and saves operation time.

A method for three-dimensional (3D) imaging of an underground goaf includes: obtaining a video image and point cloud data of an underground goaf; determining a posture transformation matrix, and aligning the video image and the point cloud data; identifying a material texture based on the video image to obtain material texture information; dividing the point cloud data into triangular meshes to form an initial 3D model of the underground goaf; mapping the material texture information onto the 3D model to form a target 3D model with a material texture attribute; calculating a bidirectional reflectance distribution function (BRDF) of the target 3D model based on the material texture attribute; simulating global illumination, and constructing a rendering equation; and making a setting to emit ray from a viewpoint, and performing ray tracing based on the rendering equation to obtain a high-brightness real scene image of the underground goaf.

An in-situ fretting corrosion fatigue testing machine based on synchrotron radiation diffraction and three-dimensional (3D) imaging includes an axial fatigue loading system, a fretting loading system, and a corrosion environment control system, where the axial fatigue loading system includes a driving device, a load control device, and a load sensing device; the load sensing device is configured to measure an axial force and a normal force in real time; the driving device is configured to drive the load control device, thereby achieving axial displacement of the load control device; the load control device is configured to carry out axial fatigue loading of a specimen; and the fretting loading system includes a fretting wear device. The testing machine achieves real-time 3D imaging characterization of wear spot and crack morphology of a material in a fretting corrosion environment, as well as characterization of a residual stress evolution law.

The invention provides a real-time three-dimensional imaging system in a thoracic surgery, and relates to the field of thoracic surgery auxiliary equipment, and the system comprises a multi-modal image collection module which is used for collecting multi-source data of tissues and organs in a thoracic cavity; the data core processor is used for processing and fusing the multi-source data collected by the multi-mode image acquisition module; the three-dimensional reconstruction module is used for generating a dynamically updated submillimeter-level precision three-dimensional model according to the processed and fused multi-source data and marking a dangerous structure and a safety boundary; and the augmented reality navigation module is used for superposing the three-dimensional model on an operation visual field through a holographic head-mounted display, and realizing real-time three-dimensional visual navigation in combination with instrument tracking and a multi-stage early warning mechanism. According to the invention, radiation-free and high-precision real-time three-dimensional visual navigation can be provided, and the precision and safety in the thoracic surgery can be ensured.

The invention discloses a road cavity volume calculation method and device based on a three-dimensional FK migration algorithm, equipment and a medium, and relates to the technical field of road cavity detection, and the method comprises the steps: obtaining three-dimensional ground penetrating radar data, and carrying out the preprocessing of the data, and obtaining target radar data; converting the target radar data to a frequency wavenumber domain to obtain frequency wavenumber domain radar data; establishing a road hierarchical velocity model, and performing hierarchical wave field extrapolation and double weight correction based on the frequency wave number domain radar data and the road hierarchical velocity model to obtain corrected wave field data; performing sparse constraint optimization imaging processing on the corrected wave field data to obtain a target imaging result; and carrying out boundary extraction processing on the target imaging result to obtain a three-dimensional cavity boundary point set, and carrying out voxelization processing based on the three-dimensional cavity boundary point set to obtain a road cavity volume. According to the invention, high-precision restoration of the shape of the road cavity and automatic extraction of the volume can be realized in three-dimensional GPR imaging.

The invention provides a three-dimensional CT imaging method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring two DR images with a vertical relation for a to-be-imaged object, and acquiring three-dimensional coordinate information of the to-be-imaged object; inputting the two DR images with the vertical relation and the three-dimensional coordinate information into a preset three-dimensional volume reconstruction model, and obtaining three-dimensional volume data of the to-be-imaged object; and slicing the three-dimensional volume data to obtain a three-dimensional CT image of the object to be imaged. According to the method, the three-dimensional volume reconstruction speed can be improved on the basis of ensuring the imaging quality, so that the high-quality three-dimensional CT image can be quickly obtained.

The invention belongs to the technical field of ultrasonic waves, and particularly relates to a nephritis physiotherapy-oriented ultrasonic cavitation control method, which comprises the following steps of: generating a renal ultrasonic image by using a three-dimensional imaging probe and collecting echo information; ultrasonic cavitation characteristics are extracted to monitor the cavitation degree in real time, a sound field and biological information are obtained by combining ultrasonic images and echo information, and calculation and normalization processing of multi-angle cavitation indexes are carried out; processing an ultrasonic image to obtain kidney position information, configuring delay parameters for a physiotherapy array, fusing normalized cavitation indexes to establish an evaluation equation, adjusting index weights according to cavitation monitoring information, guiding selection of ultrasonic amplitude-frequency parameters, and ensuring that the cavitation degree of a focusing area is in an ideal range; and encoding the time delay and amplitude-frequency parameter information to configure an excitation signal for the physiotherapy array, and transmitting ultrasonic waves. According to the method, monitoring of the cavitation effect and nephritis physical therapy can be coordinated, the medicine penetrating capacity is improved through the controllable cavitation effect, and the nephritis physical therapy effect is improved.

The invention discloses a total-space near-far field regulation and control method based on a coherent pixel super-structure surface. The method comprises the following steps: 1) constructing a nano-structure unit and a super-unit; 2) optimizing the structural parameters of the nano-structure unit according to the incident light wavelength lambda, and verifying the regulation and control effects of the super-unit I and the super-unit II; and 3) constructing a nano-structure array, wherein the nano-structure array comprises a plurality of super-units I and super-units II. Left-handed / right-handed circularly polarized light is set to be incident to the surface of the single-layer metastructure, binary nano printing of an image is achieved in a near field, and near-field nano printing intensities in a transmission space and a reflection space are complementary; different holographic patterns are respectively presented in the far-field transflective space, and the far-field transflective channels are regulated and controlled by mutually independent and continuous phases. By properly designing the single-layer nano brick, continuous and independent phase control of reflection and transmission spaces can be realized without additional equipment, far-field holographic imaging and near-field nano printing can be realized, and the single-layer nano brick can be applied to the fields of depth detection, three-dimensional imaging, optical encryption, high-resolution image storage and the like.

The invention discloses a laser energy threshold millisecond-level dynamic matching method for multi-metal fuse manufacturing, and the method comprises the steps: pre-storing a multi-metal thermophysical parameter model, calibrating a thermal signal in real time through Kalman filtering, and carrying out the online correction of a melting threshold key parameter during the switching of a material; millisecond-level thermal feedback closed-loop control is achieved through the high-frame-rate thermal imaging technology, and the laser power accurately follows the corrected melting threshold value; meanwhile, a three-dimensional imaging and deep learning segmentation algorithm is adopted, geometric information of a welding wire and a molten pool is obtained, the position and the diameter of a light spot are adjusted in real time through an adjustable optical system after the offset is calculated, and millimeter-level space registration closed-loop control is achieved; the two closed-loop systems cooperatively operate according to respective control periods, and precise dynamic matching of laser heat input in a time domain and a space domain is achieved. The problem that the adaptability of a traditional process is insufficient during multi-metal switching and complex geometric change is solved, and the forming quality, the process stability and the efficiency of manufacturing are remarkably improved.

The invention discloses a geophysical prospecting system and method for seismic survey. The system comprises a seismic source and receiving point laying module, a data acquisition module, a data processing module, a three-dimensional imaging module, a data interpretation module, a comprehensive analysis module, auxiliary equipment and an early warning module. The data processing module comprises a preprocessing module, a speed analysis superposition processing module and an offset processing module. According to the invention, data with high quality, signal-to-noise ratio and accuracy can be obtained by adding the density of the receiving points and combining the speed analysis superposition processing module to carry out superposition correction processing on the data, and meanwhile, by combining the reverse time migration technology, an underground structure can be accurately recovered, the imaging quality is improved, the subsequent interpretation and analysis work of personnel is facilitated, and the working efficiency is improved. The exploration accuracy is improved, and personnel can more accurately reveal the underground geologic structure conveniently.

The invention discloses a dam termite nest three-dimensional imaging method and system based on a ground penetrating radar, and the method comprises the steps: obtaining the three-dimensional ground penetrating radar data of a target region, and carrying out the data preprocessing, and obtaining the preprocessed three-dimensional ground penetrating radar data; performing feature extraction processing and encryption processing on the preprocessed three-dimensional ground penetrating radar data to obtain a multi-channel radar data body; based on the U-shaped network structure, constructing an ant nest imaging three-dimensional deep learning network model; and performing data imaging processing on the multi-channel radar data volume based on the ant nest imaging three-dimensional deep learning network model to obtain an ant nest imaging result based on the three-dimensional ground penetrating radar. According to the embodiment of the invention, the complex features of the ant nest and the dam structure on the three-dimensional ground penetrating radar image can be more accurately captured, and then the accuracy of ant nest imaging is improved. The method can be widely applied to the technical field of termite nest detection.

The invention relates to the field of traditional Chinese medicine diagnosis, and discloses a traditional Chinese medicine intelligent diagnosis system based on multi-source data fusion and an AI technology, and the system comprises a tongue picture collection and classification unit which is used for collecting tongue picture data of a patient through imaging equipment, carrying out the feature extraction of the tongue picture data, and obtaining a tongue picture feature data set; performing tongue picture pathological mode classification on the tongue picture feature data set based on a deep convolutional neural network to obtain tongue diagnosis identification result data; and the face diagnosis feature correlation analysis unit is used for inputting the tongue diagnosis identification result data into a multi-modal data fusion engine and carrying out face diagnosis pathological feature correlation analysis based on a graph attention network to obtain face diagnosis identification result data. The deep semantic understanding is realized by introducing a plurality of data acquisition modes such as three-dimensional imaging, thermal imaging, micro-expression recognition, spectral information and pulse condition harmonic analysis and combining advanced models such as a graph neural network, U-Net and Bi-LSTM.

The invention provides an underwater target three-dimensional reconstruction method and system based on a three-dimensional imaging sonar image, and the method comprises the steps: collecting the three-dimensional imaging sonar data of an underwater target, segmenting the sonar point cloud data through employing an optimized point cloud segmentation model, and extracting a specific target point cloud; and performing sparse reconstruction and dense reconstruction on the target point cloud in sequence, and finally realizing high-precision three-dimensional reconstruction of the target. The system comprises a data acquisition module, a preprocessing module, a reconstruction algorithm module and a visualization module, and is suitable for underwater target surveying, mapping and monitoring. The invention aims to solve the problem of insufficient reconstruction precision and efficiency of a traditional method in a complex underwater environment.

The invention belongs to the technical field of three-dimensional imaging, and particularly relates to a single-photon point cloud three-dimensional imaging method based on cross-modal feature fusion, and the method specifically comprises a point cloud data preprocessing algorithm which is used for converting single-photon laser radar echo data into a three-dimensional point cloud form, main body target extraction in the complex scene point cloud is realized, and calculation denoising processing is completed; a cross-modal feature fusion point cloud reconstruction network is designed, two-dimensional features are introduced multiple times in the reconstruction process, interaction with three-dimensional point cloud features is established, and incomplete point clouds and real complete point clouds are assisted to construct a mapping relation; a KNN segmentation coordinate filling algorithm is designed, point cloud vacant coordinates are calculated and complemented until the resolution of the point cloud vacant coordinates is matched with a two-dimensional infrared image, and two-dimensional image and three-dimensional point cloud pixel-level fusion imaging is achieved.

A system and method for determining a difficult venous access of a patient. Logic processes meta data acquired by a vasculature assessment device coupled with the patient. The meta data, e.g., vessel diameter, vessel depth, vessel wall thickness, vessel wall elasticity, tissue elasticity, tissue profusion, blood flow rate, or hydration level. The logic further determines a difficult venous access by performing an algorithm on the meta data. The algorithm is defined utilizing machine learning techniques applied to an ongoing collection data sets acquired from a plurality of systems across a plurality of patients undergoing catheter insertion events. The data set may also include patient data such as weight, age, etc. The vasculature assessment device may include ultrasound imaging, infrared imaging, molecular imaging, Raman spectroscopy, or optical coherence tomography to acquire one or both of three-dimensional imaging data and the meta data.

The invention discloses a matrix completion sparse meshless chromatography SAR (Synthetic Aperture Radar) super-resolution three-dimensional imaging method, which comprises the following steps of: constructing a multi-channel observation vector in a data field, and then further constraining an observation signal in an MMV (Modulation Modulation Virtualization) into a Hankel Lift matrix with a joint low-rank structure characteristic by utilizing an elevation consistency hypothesis between neighborhood pixels. And constructing a corresponding low-rank matrix completion model in combination with the tomographic SAR signal model. And modeling is carried out on the joint matrix completion problem. The model is solved based on a symmetric projection gradient descent algorithm, Root-Music solution is utilized to obtain elevation normalization frequency, the normalization frequency is inverted to obtain elevation information, and a scene three-dimensional imaging result is obtained by combining distance-orientation two-dimensional information of a target scene. According to the method, the elevation information of the tomographic SAR model is solved through a joint matrix completion method, tomographic SAR three-dimensional point cloud imaging is realized, a clear and complete imaging result is obtained, and a good miscellaneous point suppression effect is achieved.

The invention discloses a three-dimensional back projection imaging method and a three-dimensional back projection imaging device for an array interference SAR (Synthetic Aperture Radar), which belong to the field of SAR three-dimensional imaging, and comprise the following steps: replacing registration by utilizing a three-dimensional grid interpolation method based on a low-altitude scene three-dimensional array SAR imaging model of a polar coordinate system and a Cartesian coordinate system, expanding a sensing matrix, and utilizing compressed sensing to realize the three-dimensional back projection imaging of the array interference SAR. And the three-dimensional information is reconstructed by a CS algorithm, and high-quality three-dimensional reconstruction of an observation scene is accurately realized. According to the method, on the premise of ensuring the calculation efficiency, the resolution and accuracy of the three-dimensional imaging of the array interference SAR under the low-altitude condition are improved, the reconstruction quality of the overlay area is remarkably improved, and the three-dimensional entropy index in the measured data is improved by about 0.1.

The invention provides a multi-base satellite-borne SAR (Synthetic Aperture Radar) three-dimensional imaging method and device, and belongs to the technical field of SAR image three-dimensional imaging. The method comprises the steps of image preprocessing; geocoding and registration are carried out; removing a flat ground effect and a terrain phase; compensating an atmospheric phase error; the invention relates to high-precision tomography SAR three-dimensional imaging. The device comprises an external DEM data acquisition module, a registration module, a simulation module, a compensation module and an imaging module. According to the invention, a high-precision three-dimensional imaging result can be obtained.

The invention discloses a medical model visual interaction control method and system based on gesture recognition, and relates to the technical field of medical image interaction, and the method comprises the steps: S1, achieving the three-dimensional imaging and processing of CT and MRI image data through VTK; s2, carrying out image acquisition on an operator, and capturing a gesture action image of the operator; s3, performing gesture segmentation on the captured gesture action image by adopting a gesture segmentation algorithm; s4, analyzing the gesture change of the operator based on gesture segmentation; and S5, performing real-time control on the medical three-dimensional model according to gesture change analysis. According to the medical model visual interaction control method based on gesture recognition, a doctor can operate through natural gestures, and dependence on traditional input equipment (such as a mouse and a keyboard) is reduced. The visual interaction mode can better conform to the operation habits of doctors, the working efficiency is improved, and the visual interaction mode is particularly important in medical scenes where quick response and complex information processing are needed.

The invention discloses a weld defect detection method and device based on multi-data fusion and a medium, and relates to the technical field of data detection.A detection path of a detection robot is generated based on weld data, the detection path of the detection robot is optimized by adopting a dynamic programming algorithm and curvature fitting, and the weld defect is detected based on the optimized detection path. The method comprises the following steps: acquiring target weld joint detection data, preprocessing and fusing to obtain weld joint internal structure feature and surface geometric feature data, and constructing a three-dimensional defect projection model based on the weld joint internal structure feature and surface geometric feature data to identify weld joint defects. A moving path of a detection robot is planned according to a welding seam, so that surface morphology and internal defect information of the welding seam are synchronously acquired, data fusion and defect positioning are performed based on acquired data, three-dimensional imaging is obtained, defect detection of the welding seam is performed based on the three-dimensional imaging, the defect identification precision can be improved, and the reliability and consistency of a detection result are improved. And a more visual detection result is presented.

The invention belongs to the technical field of image processing, and mainly relates to a teenager scoliosis detection method based on three-dimensional imaging, and the method comprises the steps: obtaining multi-modal data such as a back depth map, temperature distribution, an attitude angle and a plantar pressure matrix of a detected person through a depth camera, an infrared imaging device, an I MU sensor and a plantar pressure distribution sensor; the cloud platform generates a three-dimensional point cloud and obtains a back three-dimensional curved surface model by adopting a Poisson surface reconstruction algorithm, overall attitude correction is carried out by combining an attitude angle and pressure gravity center shift, and a thermal correction model of local deformation is constructed based on a thermodynamic diagram; automatically identifying spine segment mark points through a deep learning algorithm, fitting a spine center line, calculating a Cobb angle, judging the scoliosis degree and outputting an analysis report; according to the method, X-ray imaging is not needed, the detection safety is high, attitude, mechanical and thermal information can be fused, artificial attitude interference is reduced, and the method is suitable for early screening and dynamic reexamination of teenagers.

The invention discloses a sensor calibration test system and a calibration test method for UUV intelligent perception, belongs to the technical field of underwater robots, and aims to solve the problems that the capability evaluation of the UUV intelligent perception system is difficult to realize, the credibility, the reliability and the accuracy are poor, and the UUV intelligent perception system cannot be fully matched with the actual application environment and cannot be optimized due to the existing underwater multi-mode comprehensive perception calibration mode. And the development and improvement of the intelligence of the UUV are directly influenced. The sensor calibration test system can simulate various motion modes of the underwater vehicle and the underwater target in navigation, so that a large number of calibration samples are formed, the three-dimensional imaging sonar, the underwater camera and the magnetometer can realize calibration of working parameters based on the underwater acousto-optic magnetic comprehensive beacon arranged on the underwater target, and the calibration precision is improved. After sensor calibration is completed, the system can be used for testing the calibration effect of the sensor, and the number of times and cost of sea test calibration are effectively reduced.

The invention relates to a single-photon laser radar three-dimensional imaging system and method. An optical fiber laser is used for actively illuminating an imaging target; the single-photon APD array detector is used for receiving a laser echo signal reflected by a target; the near-infrared detector is used for realizing aiming; the upper computer is used for parameter setting and data receiving of the optical fiber laser, the single-photon APD array detector and the near-infrared detector, receiving active laser three-dimensional imaging data in a three-dimensional imaging state and realizing real-time display of a depth image and an intensity image; and the information processing board card is used for realizing synchronous triggering of the fiber laser and the single-photon APD array detector and data communication between the upper computer and the fiber laser and the single-photon APD array detector, and realizing preprocessing and three-dimensional reconstruction of APD data based on a time correlation single-photon counting method and in combination with space-time correlation characteristics of laser echo signals. According to the invention, the problem of insufficient detection capability of a single-photon laser three-dimensional imaging method under all-weather and low-signal-to-noise-ratio conditions is solved.

The invention relates to a point cloud-image-based three-dimensional imaging method and system, and belongs to the technical field of optical imaging. Comprising the following steps: inputting an image, and carrying out two-dimensional image instance segmentation on the image to obtain a two-dimensional mask; extracting a point cloud corresponding to the two-dimensional mask from the three-dimensional point cloud data of the image, processing the point cloud and performing three-dimensional modeling to obtain a three-dimensional research target; triangulation is carried out on the three-dimensional research target, and discrete point cloud is converted into a grid structure; projecting the grid structure into a two-dimensional coordinate system, and searching intersection points of edges of triangles in the grid structure and image edge information; wherein the image edge information is obtained by performing edge detection on the two-dimensional research target; the two-dimensional research target is obtained by extracting a two-dimensional mask; and adding the intersection points into the point cloud structure and performing triangulation to complete three-dimensional imaging. According to the method, the three-dimensional space information and the texture features can be obtained at the same time, the difference between the point cloud and the image data scale is reduced, and the loss of the texture information is reduced.

The invention discloses a single-frame real-time three-dimensional imaging method based on deep learning. The method comprises the following steps: constructing a lightweight phase recovery network model based on a physical model; building a multi-vision structure light stripe projection system; and constructing a training data set, completing training of the lightweight phase recovery network model, and deploying the lightweight phase recovery network model by using TensorRT. Three wrapped phase images are obtained in real time through parallel reasoning of three monochromatic view angles; unwrapping the wrapped phase into an absolute phase by using a multi-view geometric constraint and three-dimensional phase matching algorithm; and generating a three-dimensional point cloud with color texture information through phase-height mapping and a color image. According to the method, the deep learning technology and a traditional fringe projection physical model are combined, rapid phase acquisition can be completed only through a single frame of image, motion interference is overcome, and online real-time high-precision three-dimensional imaging of a complex dynamic scene is achieved.