427 results about "Triangulation" patented technology

The invention belongs to the technical field of super high-rise building three-dimensional reconstruction, and particularly relates to a multi-source data fusion super high-rise building group live-action three-dimensional model construction method. According to the method, an initial three-dimensional model is generated through a series of processing such as aerial triangulation encryption and triangulation network construction based on multi-source image data, in the process of recognizing a fuzzy region and performing data supplementary collection, regions with texture loss and structure distortion in the initial three-dimensional model can be positioned, supplementary collection requirements are determined according to characteristics of different regions and a preset threshold value, and the recognition accuracy of the initial three-dimensional model is improved. The method comprises the following steps of: performing oblique photography on an unmanned aerial vehicle to acquire data in a supplementary manner, fusing the data with original data, extracting a building structure contour, matching high-resolution texture data, performing texture binding and processing and the like to form a building monomer model, and performing spatial position and texture fusion on the building monomer model and a process three-dimensional model to generate a regional three-dimensional live-action model. And finally, splicing and fusing the three-dimensional live-action models of all the areas to form a complete super high-rise building group live-action three-dimensional model.

The invention discloses a construction site three-dimensional scene reconstruction method based on an unmanned aerial vehicle image and a monitoring video. The method comprises the following steps: acquiring a construction site scene multi-view image; a sparse three-dimensional point cloud and a camera pose are generated through a feature matching and motion recovery structure algorithm, and dense reconstruction is carried out to obtain a global three-dimensional point cloud; aligning the global three-dimensional point cloud with a world coordinate system by using geographic position information; estimating the position of a shooting camera in the three-dimensional point cloud, sampling a candidate view angle and rendering a virtual RGB image; based on two-dimensional feature matching of the shot image and the virtual RGB image, internal parameters and external parameters of the shooting camera are iteratively solved through triangulation and a pose optimization algorithm; monocular depth estimation is carried out on the shot image, and the shot image is converted to a measurement scale through static region depth alignment; and projecting the depth of the shot image to the three-dimensional point cloud, updating the dynamic object in real time, and fusing the dynamic object into a complete three-dimensional scene model. The method has the advantage that the real-time three-dimensional reconstruction of the dynamic scene of the construction site is realized.

The invention discloses an unmanned aerial vehicle camera attitude estimation optimization method and device, and relates to the technical field of unmanned aerial vehicles. The method comprises the following steps: acquiring data by using an unmanned aerial vehicle carrying various sensors, preprocessing, carrying out feature extraction and matching on preprocessed image data, removing mismatching points, and based on an initial point cloud, carrying out sparse reconstruction in an incremental expansion and bundle adjustment optimization stage; integrating the re-projection error term, the flight path constraint, the epipolar geometric constraint and the triangulation constraint into a target function; constructing a model for predicting the pose correction based on the deep residual convolutional neural network, and taking the initial pose of the camera and the corresponding local image as input; and adjusting the weight of each constraint in the target function based on the predicted pose correction and pose confidence, and minimizing the target function to improve the precision of unmanned aerial vehicle camera pose estimation. The problem of reconstruction scene deviation caused by inaccurate camera attitude estimation in the prior art is solved.

The invention particularly relates to a binocular vision-based three-dimensional reconstruction method, which comprises the following steps of: calibrating a binocular camera based on an improved Zhang Zhengyou calibration method to obtain internal and external parameters and a distortion coefficient of the camera; performing stereo correction on the image by using the internal and external parameters of the camera and the distortion coefficient obtained by calibration, so that the binocular image meets an epipolar constraint condition; a multi-strategy optimized semi-global stereo matching algorithm is adopted to process the image after stereo correction, and a disparity map is generated; based on the generated disparity map, generating a three-dimensional point cloud through a triangulation principle; carrying out anti-interference processing and registration optimization on the three-dimensional point cloud; and performing global splicing on the three-dimensional point clouds subjected to anti-interference processing and registration optimization based on a sequential registration error sharing strategy to complete three-dimensional reconstruction. According to the method, the key problems of large calibration error, weak texture matching failure, point cloud noise sensitivity and registration accumulative error in a traditional method are solved, and the reconstruction precision and stability are remarkably improved.

The invention discloses a farmland precise fertilization control method based on multi-source data fusion and deep learning, and the method comprises the steps: obtaining the multi-dimensional heterogeneous data of a target farmland in real time, including the crop spectrum time series data of a satellite image, the ion concentration data collected by a soil sensor network, and the microenvironment time series monitored by a meteorological station; and constructing a Delaune triangulation network spatial index, and re-sampling satellite image data to be matched with a soil sensor network space. Calculating a time-varying mutual information entropy, extracting related microenvironment parameters as coupling factors, combining the coupling factors with soil basic parameters to form a three-dimensional feature matrix, and converting the three-dimensional feature matrix into a growth period feature vector fused with time-space correlation; the collaborative decision model is input, the main branch predicts the basic fertilization amount, the auxiliary branch detects the ion concentration space mutation area and corrects the fertilization amount, a fertilization control instruction is output, and the fertilization device is controlled to conduct precise fertilization. The problem that fertilization control cannot be accurately and efficiently performed on farmland in the prior art is effectively solved.

The invention discloses a multi-target tracking method, system and device, a medium and a product, and relates to the technical field of computer graphic vision, and the method comprises the steps: based on a plurality of single-view two-dimensional images, employing a lightweight key point detection model to extract human body two-dimensional key point coordinates under different views; based on the camera parameters corresponding to different visual angles and the human body two-dimensional key point coordinates under different visual angles, performing three-dimensional reconstruction on the human body key points by using a triangulation method to obtain a three-dimensional reconstruction model; projecting the three-dimensional reconstruction model, and determining a projection frame corresponding to each target in the tracked area; and a tracking algorithm and Kalman filtering are combined to complete real-time tracking of a plurality of targets in the tracked area. According to the method, the three-dimensional target tracking problem is reduced into the two-dimensional target tracking problem based on the projection frame of the three-dimensional reconstruction model relative to the horizontal plane, the accuracy and robustness of the model can be improved in a multi-target tracking scene, and meanwhile, the calculation amount is reduced.

The invention provides a low-airspace public route construction method, device and equipment, and relates to the technical field of aircraft airspace route planning. The method comprises the following steps: determining a plurality of target candidate nodes corresponding to a city based on ground traffic topological characteristics of the city corresponding to a low airspace and spatial distribution characteristics of low-risk ground features; performing triangulation on the plurality of target candidate nodes to obtain an initial edge set; wherein the initial edge set comprises a plurality of initial edges; performing sparse processing on the plurality of initial edges based on a greedy tensor graph algorithm, and determining a plurality of target edges from the plurality of initial edges; wherein the length of the shortest path between the two nodes of the target edge is greater than the greedy tensor coefficient times of the Euclidean distance between the two nodes; and constructing a low-airspace public route based on the plurality of target edges. By adopting the technical scheme provided by the invention, the utilization efficiency and safety of the low airspace can be effectively improved by constructing the unified low airspace public route.

The invention discloses a submarine topography reconstruction system and method based on optical mobile measuring and scanning, and relates to the technical field of ocean exploration, and the system comprises the following units: an image collection unit, which is used for coordinating the emission of 532nm pulse laser and the collection of a gating camera image through a synchronous sequential circuit, a triangulation measurement optical structure with separated emission and reception is adopted, and a submersible can be carried for mobile measurement and scanning; the system calibration unit is used for carrying out joint calibration on camera parameters and a laser plane so as to determine system calibration parameters, so that the spatial position of a laser stripe accurately corresponds to the actual coordinate of the target surface; and the image processing unit is used for preprocessing the image acquired by the system and further extracting the coordinates of the center line of the laser stripe in the preprocessed image. According to the invention, adjacent splicing can be carried out through continuously collected laser stripe images to construct two-dimensional submarine landform information, and three-dimensional reconstruction of submarine topography can be carried out by using generated point cloud data.

The invention relates to the technical field of data processing, and provides a BIM model continuous grid bottom surface extraction method, device and equipment and a storage medium, according to the scheme of the invention, grid bottom surface extraction is carried out based on a user-defined data structure after BIM model triangularization, the influence of a professional design software production environment and a multi-source heterogeneous storage format is eliminated, and universality is achieved; according to the method, the cleaned and corrected triangularized grid model is subjected to space division and an elevation extraction algorithm, so that the grid bottom surface extraction efficiency is greatly improved; according to the method, curved surface reconstruction is carried out according to the spatial point cloud normal set and the point cloud data set, so that the construction accuracy of grid bottom surface extraction in the projection direction is ensured, a finer and more continuous geometric expression is provided, and the problem of model bottom surface image missing is solved.

The invention relates to the technical field of three-dimensional digital modeling, in particular to an automatic real-time three-dimensional digital modeling method and system for a dike. The method comprises the following steps: collecting first image data of a dike area, and setting a three-dimensional coordinate system of the dike area; evaluating a plane median error and an elevation median error of the first image data, and obtaining field acquisition precision based on the plane median error and the elevation median error; adjusting shooting parameters of the unmanned aerial vehicle according to the field acquisition precision, and acting the adjusted shooting parameters of the unmanned aerial vehicle on the unmanned aerial vehicle; acquiring second image data of the dike area through the adjusted unmanned aerial vehicle; executing spatial triangulation calculation on the second image data, and generating aerial triangulation calculation result data; and performing three-dimensional model reconstruction based on the aerial triangulation result data to obtain a dike three-dimensional digital model. According to the method, the frequency and the precision of obtaining the geometric information of the dike can be improved, and high-resolution and dynamically-updated three-dimensional modeling is realized.

The invention provides an airborne point cloud building contour point extraction method based on a constraint triangulation network and semantic ring analysis, and belongs to the field of airborne laser radar data processing, and the method comprises the steps: obtaining an airborne laser radar point cloud data set of a to-be-processed region; performing classification processing by using a filtering algorithm to obtain a surface point set and a non-surface point set; building candidate seed points are extracted, and building point clouds are extracted; a Delaunay triangulation network is constructed based on the building point clouds, and constraint is carried out based on the distance between the point clouds; constructing a concurrent triangle set, and extracting contour points and contour connecting edges; and constructing a topological graph, performing traversal search on the topological graph, determining the minimum inclusion rectangle of the closed loop, and judging the contour point type corresponding to the closed loop according to the geometrical shape parameter and the spatial distance parameter of the minimum inclusion rectangle. According to the method, the triangulation network is constructed by using the disordered contour points, and the sequence relationship and semantic information between the points are considered, so that accurate extraction of the semantic contour points is realized.

The invention relates to the technical field of highway engineering safety monitoring, in particular to a highway subgrade three-dimensional deformation monitoring system based on unmanned aerial vehicle oblique photography, and the system comprises an unmanned aerial vehicle oblique photography module which adopts a five-lens synchronous shooting strategy to realize the omni-directional coverage of a subgrade; the three-dimensional point cloud generation engine generates a high-precision three-dimensional point cloud model through feature extraction, registration and triangulation strategies; the deformation field analysis platform models a roadbed surface into a parameterized Riemannian manifold based on a differential geometry theory, captures deformation dynamic characteristics through multi-scale curvature flow analysis, and identifies potential risks by using topological evolution characteristics of deformation singular points; and the risk evaluator evaluates the risk level based on the singular point density, the change rate and the topological stability and generates early warning information. According to the invention, millimeter-level accurate monitoring of roadbed deformation is realized, various deformation modes from micro-cracks to large-scale settlement can be captured, the potential landslide risk is early warned 30-45 days in advance, and the false alarm rate is significantly reduced.

A navigation system and method are disclosed for operation in GPS-denied environments using quantum-inspired sensor fusion, dynamic virtual anchor points (VAPs), and predictive environmental modeling. The system represents multiple position hypothesis using wavefunction-like expansions and integrates VAP-based triangulation for drift correction. A predictive modeling module ingests solar, geomagnetic, and environmental data to proactively adjust sensor weighting. A cybersecurity module employs quantum-algebraic key generation and location-derived ephemeral keys to secure inter-device communication. The system includes an augmented reality (AR) interface to visualize and edit anchor references, and a neurofeedback module that adapts the AR interface based on real-time physiological signals from the user. The method further enables anchor optimization via AI-driven repositioning and supports low-power edge execution using approximate amplitude filtering. Additional modules may include fractal antennas, neuromorphic processors, and adaptive forecasting layers to maintain positional accuracy and user experience in subterranean, multi-floor, or magnetically complex environments.

The invention provides a high-precision urban live-action three-dimensional model generation method and system and a storage medium. The method comprises the following steps: arranging photo control points in a target area and performing measurement; acquiring inclined image data of the target area by using the unmanned aerial vehicle; acquiring original point cloud data of the target area by using a laser scanner; performing aerial triangulation calculation on the inclined image data in combination with ground control point data to obtain aerial triangulation encrypted data; registering the original point cloud data in combination with the ground control point data, and then preprocessing the original point cloud data to obtain laser point cloud data; carrying out fusion reconstruction on the aerial triangulation encryption data and the laser point cloud data to generate an initial three-dimensional model; performing fine processing on the initial three-dimensional model to generate a high-precision three-dimensional model; according to the method, water surface cavities can be automatically repaired and efficient and intelligent color homogenization can be realized when the live-action three-dimensional model is constructed, so that the geometric accuracy and visual quality of the model are effectively improved, and engineering-level application requirements are met.

The invention relates to the technical field of underwater topographic surveying and mapping, in particular to a sea area water taking channel scanning survey method and system based on multi-beam measurement, and the method comprises the following steps: constructing a rigid support, fixing a depth finder through a three-way cable fastening device, and building a Boolean parameter model; sound velocity, tide level and original echo data are collected; performing space-time registration, coordinate conversion and filtering denoising on the data to generate corrected water depth; and constructing an irregular triangulation network by using hard boundary constraint, generating a digital elevation model, and extracting a siltation area. According to the invention, multi-beam wide sector scanning and multi-sensor attitude correction technologies are fused, a limited water area full-coverage measurement system is constructed, and the problems of terrain blind areas and detail loss are solved. A boundary constraint reconstruction algorithm is utilized to realize closed-loop processing from coordinate reference unification to micro-landform restoration, the accuracy of channel bottom pit capture and edge topography expression is improved, and data support is provided for sedimentation analysis.

The invention provides a structured light projector calibration method and system and a medium, and the method comprises the steps: projecting a multi-frequency stripe pattern to a target region based on an MEMS micromirror array module, obtaining a distorted image sequence, and carrying out the phase decoding, and obtaining a phase diagram corresponding to each frequency; resolving the phase diagram based on a phase shift method and an optical path triangulation principle to obtain a preliminary three-dimensional point coordinate; constructing a neural network model and a calibration sample set, obtaining a real three-dimensional coordinate by using a standard calibration plate or a known curved surface, and calculating the deviation between the initial three-dimensional point coordinate and the real three-dimensional coordinate to obtain a training sample set; and training the neural network model according to a training sample set based on an Euclidean distance loss function, outputting a three-dimensional offset compensation amount according to the neural network model, correcting the initial three-dimensional point coordinates, and realizing an end-to-end error self-compensation mechanism through the neural network model, so that deviation compensation is effectively performed on the three-dimensional point coordinates, and the accuracy of the three-dimensional point coordinates is improved. And the three-dimensional reconstruction precision is improved.

The invention discloses an indoor and outdoor fine three-dimensional modeling method based on multi-modal data fusion. The method comprises the steps that unmanned aerial vehicle close-range photography, airborne laser scanning and ground supplementary photography are carried out on a building in a low-altitude area, and a first outdoor photo data set, a first laser point cloud data set and a POS data set of the building are obtained; continuously collecting at an indoor entrance through a laser SLAM mobile scanning system and a panorama camera according to a pre-planned route to obtain a second indoor photo data set and a second laser point cloud data set of the building; aerial triangulation adjustment calculation of a multi-source data set is carried out under the assistance of a POS data set, and an indoor and outdoor integrated fine surface three-dimensional model is automatically constructed. According to the method, the indoor and outdoor integrated surface three-dimensional model of the large building can be duplicated, the element cosmic space base scene is realized, and data application is provided for the industries of element cosmic scenes, indoor navigation, surveying and mapping and the like.

The invention discloses a digital twin modeling method and system based on binocular vision and target dynamic tracking, and the method comprises the steps: constructing a binocular camera system, completing the calibration of internal parameters, distortion and external parameters, and building a coordinate system mapping relation; synchronously collecting and correcting target images, extracting coordinates of feature points, and then removing anomalies and distinguishing multiple targets; the parallax of the feature points is calculated, three-dimensional coordinates are obtained through triangulation, and optimized target point cloud is generated; solving target space poses through a PNP algorithm, and realizing single / multi-target dynamic tracking in combination with time sequence difference; carrying out anomaly detection and smoothing processing on the pose sequence, and constructing a weighted error model closed-loop optimization feature recognition parameter; transmitting pose data to realize virtual and real synchronous visualization of the workpiece; the workpiece space relation and the collision risk are monitored, an alarm is given, and data are stored for backtracking analysis. According to the method and the system provided by the invention, high-precision dynamic measurement, attitude tracking and assembly process digitization and visualization of a complex workpiece assembly process are realized.

An aerial vehicle configured for operating within indoor or outdoor spaces is equipped with acoustic sensors for detecting reflections of sound, or echoes, from objects. Distances and bearings to such objects may be calculated based on such echoes. The echoes may be reflections of sound actively emitted by the aerial vehicle, such as by a speaker, or sound radiating from operating components aboard the aerial vehicle, such as rotating motors or propellers. The echoes may be captured by multiple sensors such as microphones provided around the aerial vehicle and used to calculate distances or bearings to the objects, such as by trilateration, triangulation, or in any other manner. Such distances or bearings may also be utilized along with distances or bearings determined from cameras, range sensors, or other systems, and used to generate a navigation map of the space, or compared to a navigation map generated for that space.

The invention discloses a multi-view image Gaussian reconstruction method and system guided by LiDAR point cloud. The method comprises the following steps: step S1, realizing accurate registration of LiDAR point cloud and a multi-view image in the same earth-centered earth-fixed coordinate system through GNSS constrained aerial triangulation, and uniformly carrying out center-of-gravity normalization to ensure space consistency and numerical stability; s2, estimating surface normal and scale parameters based on the local geometric features of the LiDAR point cloud, constructing a Gaussian ellipsoid consistent with the local geometry, and realizing Gaussian ellipsoid initialization of geometric perception; and S3, generating a sub Gaussian ellipsoid according to the Gaussian gradient and the tangent plane direction, and improving the modeling density and geometric continuity of the detail region through local encryption and parameter inheritance. According to the method, the fusion of LiDAR point cloud high-precision geometry and multi-view image texture information is realized, the geometric precision, the structural integrity and the detail expression capability of three-dimensional reconstruction are effectively improved, and the method is particularly suitable for high-precision live-action three-dimensional modeling of unmanned aerial vehicle multi-view images.

A medical-device navigation system includes, in some embodiments, an electromagnetoresponsive (“EMR”) element, a magnetic interrogator, and a console. The magnetic interrogator generates an external magnetic field, transduces resonance-based responses of the EMR element thereto, and provides response data for the EMR element as an elongate portion of a medical device including the EMR element moves through the external magnetic field. The console instantiates medical-device navigation processes including a data-acquisition process, a triangulation process, and a plotting process for navigating the elongate portion of the medical device as it is advanced through the external magnetic field to a target location. The data-acquisition process acquires the response data from the magnetic interrogator over time, the triangulation process triangulates the EMR element with respect to magnetic sensors of the magnetic interrogator over time, and the plotting process plots a location of the EMR element on a display screen of the console over time.

The invention provides a slope excavation engineering quantity calculation system and method based on point cloud, and the method comprises the steps: reading the slope geological data of hydropower engineering to construct an initial three-dimensional model, and collecting the multi-stage point cloud data through a three-dimensional laser scanner; performing equidistant gridding on the point clouds of the model region according to an X / Y axis, calculating the spatial similarity and color similarity of the point clouds in grids, and dividing sub-data sets according to threshold values; fitting an excavation surface through a Delaunay triangulation network, calculating an XY plane projection area, and calculating an average Z-direction distance from a subset to the surface of the initial model; the node weight of the triangulation network is corrected by fusing rock stratum interface parameters, finally, the excavation engineering amount is dynamically output through summation of the product of the projection area of each subset and the average distance, and when the deviation of adjacent stages exceeds 10%, cross validation is conducted in combination with a profile method. According to the method, the precision and the real-time performance of slope excavation engineering quantity calculation can be improved, and automatic integration of lithologic characteristics and mechanical attributes is realized.

The invention discloses a near-ground distance measurement method based on virtual large baseline four-eye vision, a medium and equipment, and the method comprises the steps: synchronously obtaining four images when a lifting appliance enters a near-ground operation range; based on the calibration relation between the cameras, the high-altitude images are respectively projected and transformed to the visual angles of the corresponding lifting appliance cameras and fused, two virtual camera images are generated, and therefore a virtual large base line far exceeding the physical distance is constructed; performing three-dimensional correction and cutting on the virtual image pair to obtain a row-aligned three-dimensional image pair; performing feature matching and triangulation on the virtual image pair to generate a sparse reference depth map; and inputting the stereo image pair and the sparse depth map into a pre-trained depth estimation neural network model together, outputting a dense depth map, and converting the dense depth map into a coordinate system taking the lifting appliance as an original point to obtain a vertical distance. According to the invention, the ultra-large baseline is virtually synthesized by using the existing camera, the remote distance measurement precision is improved, the cost is low, and the reliability is high.

The application provides a three-dimensional reconstruction method based on binocular stereo matching, and relates to the technical field of binocular stereo vision. The method combines binocular stereo matching algorithm, triangulation algorithm and surface texture mapping, and can realize surface reconstruction of scene objects in different environments. After stereo calibration is performed on a binocular camera, the internal and external parameters of the binocular camera are obtained, stereo correction is performed, then an image disparity map of the corresponding scene object is generated according to an optimized semi-global stereo matching algorithm, after the disparity information is obtained, the point cloud information converted by the object disparity is triangulated on the surface according to the triangulation algorithm, and finally three-dimensional surface reconstruction of the object is realized through the texture mapping technology. The application can reduce the influence of noise in the disparity map generation process, i.e. the semi-global stereo matching algorithm, improve the accuracy of the disparity information, and complete the three-dimensional surface reconstruction task of the object with little sacrifice of time performance.

The invention discloses a binocular vision-based fish body quality non-contact estimation method, which comprises the following steps of: in a land-based facility circulating water high-density culture environment in which a fish body freely swims and is easy to block, firstly, obtaining a fish head local image through fish head region segmentation, and carrying out position alignment and scale normalization processing on the fish head local image; constructing a stable fish head geometric anchor point; then, the fish head anchor point is used as condition input, and a generative model is used for inferring and complementing the overall shape of the fish body so as to recover a continuous geometric structure of the fish body; on the basis, binocular stereo vision is combined to carry out stereo matching on key points of the head and the tail of the fish body, and the length of the fish body is obtained through triangulation; finally, based on the mapping relation between the body length and the quality, automatic estimation of the fish body quality is achieved, manual contact with the fish body is not needed, stable and automatic measurement of the fish body quality can be achieved in a complex breeding scene, and the method has the advantages of being high in adaptability, low in stress risk and high in application value.

The invention discloses a power cable outer sheath fault positioning method, and belongs to the technical field of cable fault positioning. Aiming at the problems of poor adaptability, weak anti-interference capability and low positioning precision of the existing cable outer sheath fault positioning technology, the method comprises the following steps of: acquiring horizontal and vertical components of an electromagnetic signal by deploying an array sensor, and obtaining pure vector distribution through Fourier transform and wavelet denoising processing; judging coordinates of an abnormal point according to an amplitude threshold value and a phase ratio, and determining a fault cluster center by adopting K-means clustering; and fusing the environmental data, refining the position through iterative filtering, comparing and confirming a final fault point in combination with triangulation and historical data, and generating a vector distribution map and a diagnosis report. According to the invention, high-precision and anti-interference positioning and visual diagnosis of cable faults in a complex environment are realized.

The invention provides a road element recognition method and device based on a vehicle-mounted point cloud image and a storage medium. The method comprises the following steps: adding time identifiers for an image sequence, point cloud data and original navigation data under a unified time reference; carrying out inertia and satellite integrated navigation calculation according to the original navigation data to obtain vehicle pose information at each time point; road elements in the image are detected and recognized, and the two-dimensional position and attribute text information of each road element in the image are obtained; performing cross-frame correlation tracking on the same road element to obtain a pixel coordinate sequence of the road element in the multi-frame image and a corresponding camera pose sequence; three-dimensional coordinates of all the road elements in the geographic coordinate system are obtained through triangulation calculation, and road element data containing the three-dimensional coordinates and attribute information are output. According to the invention, the automatic identification and three-dimensional positioning precision of the road elements can be improved, the large-range acquisition efficiency is improved, and unified structured road element data is formed.

The invention relates to a spoil field three-dimensional form change analysis method, which comprises the following steps: constructing an air-space-ground collaborative multi-scale three-dimensional monitoring network by adopting an unmanned aerial vehicle carrying a laser radar system; dynamic construction of a multi-period digital elevation model and a digital terrain model is realized through a weighted fusion algorithm based on point cloud density difference and an improved progressive triangulation network encryption algorithm; performing time sequence alignment on the digital terrain models in different periods, and constructing a digital elevation difference model; and through a digital elevation difference model and a self-adaptive threshold change detection technology, the space-time differentiation characteristics and evolution rules of a slope curvature sudden change area, a surface roughness abnormal zone and a deformation rate of the spoil site are disclosed. According to the scheme provided by the invention, high-precision three-dimensional form dynamic modeling and deformation process precise monitoring of the spoil ground can be realized, and reliable technical support is provided for ecological safety situation assessment and geological disaster advanced early warning of the spoil ground.

The invention relates to a method for determining the position and / or orientation of tools of construction machines in a construction area, comprising the steps of: attaching at least one stereo camera to at least one construction machine or to a movable carrier, such that the stereo camera can detect at least one detection region within the construction area, preferably a working region of the construction machine, providing at least one reference point, the position of which is known relative to a predefined 3D world coordinate system and which can be recognised in the images of the stereo camera, in the detection region of the at least one stereo camera, calibrating the at least one stereo camera on the basis of the detection of the at least one reference point and triangulation in order to ascertain a transformation between the 3D world coordinate system and a 2D image coordinate system of the at least one stereo camera, preparing a virtual digital 3D terrain model of the construction area by means of digital image processing, in particular stereoscopy, and image recognition on the basis of the detection of the construction area by means of the at least one stereo camera, and representing predetermined working positions and detected actual tool positions and / or actual tool inclinations of the tool of the at least one construction machine in the virtual digital 3D terrain model.

The invention relates to the technical field of earthwork calculation, in particular to an earthwork calculation method based on an unmanned aerial vehicle aerial survey technology. According to the technical scheme, the method comprises the steps of image control point layout and data acquisition, unmanned aerial vehicle image data acquisition, aerial triangulation processing and model generation. Based on an unmanned aerial vehicle aerial survey technology, image control points are scientifically arranged to collect high-precision coordinates, high-quality image data are obtained, a high-precision model is generated through aerial triangulation processing, the precision is strictly verified, data are extracted through professional software to construct an optimized DTM model, and precise earth-rock volume calculation is achieved; a calculation result is encrypted and stored by means of a block chain and is in butt joint with a construction management system, and a GIS platform and a BIM model are combined to generate a visual progress diagram, simulate slag yard capacity early warning and the like, so that the precision and efficiency of earth-rock calculation are comprehensively improved, powerful support is provided for engineering construction management, auditing tracing and ecological restoration decision, and the method is suitable for popularization and application. And the scientificity and informatization level of project management are obviously improved.