775 results about "Photogrammetry" patented technology

The invention provides an unmanned aerial vehicle route layout method and device for complex terrains, equipment and a medium, and relates to the technical field of unmanned aerial vehicle aerial photogrammetry. The method comprises the following steps: carrying out preliminary region division on a terrain region to be surveyed, and determining a plurality of region units; clustering the area units according to topographic observation data to obtain survey sub-areas; determining a survey priority corresponding to each survey sub-region, and matching a basic flight route corresponding to the unmanned aerial vehicle according to the survey priority; and splicing the different types of basic flight routes corresponding to the survey sub-regions, and performing optimization adjustment on the spliced basic flight routes to obtain a flight route of the target unmanned aerial vehicle so as to perform topographic survey on the topographic region to be surveyed. According to the technical scheme, the route planning of the unmanned aerial vehicle can adapt to various types of landform features, and the safety and aerial survey efficiency of the unmanned aerial vehicle are ensured while the integrity and accuracy of aerial survey data are improved.

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

The invention discloses a building health state detection system, and relates to the technical field of photogrammetry and image processing, the system firstly obtains four-dimensional space-time coordinate data of a plurality of monitoring points on a target building based on satellite image analysis, constructs a four-dimensional space-time network model containing spatial topology and time sequence evolution information according to the four-dimensional space-time coordinate data, and then obtains a four-dimensional space-time network model containing space topology and time sequence evolution information; the system maps network model nodes to a predefined standard reference network associated with a local gravity direction, then, the system analyzes dynamic relevance in the four-dimensional network model by adopting a graph self-attention network, and meanwhile, calculates relative relation changes of monitoring points relative to the predefined standard reference network through geometric analysis; the deformation interpretation module distinguishes and determines internal relative deformation, overall displacement and absolute posture change (including settlement and inclination) of the building according to the two types of analysis results and by referring to surrounding environment information, and the state evaluation module integrates the information to generate a health state report containing risk levels.

The invention discloses a road slope modeling method based on an unmanned aerial vehicle inspection route, and relates to the technical field of unmanned aerial vehicle inspection. The method comprises the following steps: measuring the road slope length, the landform and the geological complexity, and selecting an adaptive unmanned aerial vehicle type and sensor combination according to the road slope length, the landform and the geological complexity; planning unmanned aerial vehicle surface inspection and shallow geological exploration routes, ensuring space matching, and synchronously obtaining high-resolution images and ground penetrating radar data; and processing image data through a photogrammetry technology, generating a digital elevation model and an orthophoto map, and combining to construct a three-dimensional model of the earth surface. Geophysical inversion is carried out on the ground penetrating radar data, reflection features are extracted and projected to the ground surface three-dimensional model, and space correlation between the ground surface and a shallow layer structure is established; the reflection features are digitalized and geometrically reconstructed into three-dimensional surface elements, the three-dimensional surface elements are embedded into an earth surface model to form a three-dimensional geologic body model, time dimensions are introduced, and a dynamic evolution model is constructed. According to the dynamic evolution model, the dynamic analysis of the slope stability is realized.

The invention discloses a live-action three-dimensional model construction method and system, a storage medium and equipment, and belongs to the technical field of three-dimensional modeling, and the method comprises the steps: laying control points in a region needing collection, and collecting ground control point data; acquiring inclined image data by using the unmanned aerial vehicle, and performing aerial triangulation calculation on the inclined image data in combination with the ground control point data to obtain aerial triangulation encrypted point cloud data; acquiring point cloud data by using a laser scanner, registering the point cloud data in combination with ground control point data, and then preprocessing the point cloud data to obtain laser point cloud data; carrying out fusion reconstruction on the aerial triangulation encryption point cloud data and the laser point cloud data to generate a three-dimensional model; and performing fine processing on the three-dimensional model to generate a high-precision model. According to the method, the three-dimensional laser scanning technology is used for assisting oblique photogrammetry, ground control points are used for unifying coordinates and repairing missing point clouds of a blind area, the integrity of the point clouds of an oblique photogrammetry shielded area can be guaranteed, and the fineness of the model is improved.

The invention provides an unmanned aerial vehicle oblique photogrammetry data intelligent processing method and system, and relates to the technical field of unmanned aerial vehicle photogrammetry, and the method comprises the steps: carrying out the preprocessing of an oblique photogrammetry original image, obtaining the exterior orientation elements of a camera, carrying out the scene semantic segmentation through a deep convolutional neural network, adaptively determining the optimal three-dimensional reconstruction parameters of each region, and obtaining the optimal three-dimensional reconstruction parameters of each region. On the basis of multi-view image matching, feature point parallax information is calculated to generate dense point clouds, different areas are processed by adopting an adaptive grid division strategy and a corresponding noise reduction algorithm, and finally, a three-dimensional scene model with real textures is constructed, so that high-precision three-dimensional reconstruction of different scene areas is realized.

The invention discloses a method for measuring an attitude angle of a free throwing object in a wind tunnel test through a binocular system, and belongs to the field of aerodynamics tests based on a photogrammetry technology. Comprising the steps that a binocular system is arranged in a wind tunnel, and internal and external parameters of the binocular system are calibrated through a cross scale; reconstructing the surface mark points of the calibration plate by photogrammetry outside the wind tunnel and establishing a local coordinate system; placing a calibration plate in the wind tunnel, wherein each vector of a local coordinate system is parallel or vertical to an incoming vector, and calibrating a wind tunnel coordinate system by adopting a resection method; carrying out photogrammetry and initial pose installation on mark points on the surface of a thrown object; acquiring each state image of the thrown object and reconstructing the three-dimensional coordinates of the surface mark points; taking the attitude angle of the thrown object as 0 degree as a reference state, and comparing the rigid body transformation relationship between the blowing state point cloud and the reference state point cloud to obtain attitude angle data. Alignment of a wind tunnel coordinate system and a binocular system coordinate system can be achieved, limitation of the appearance of the thrown object is avoided, and attitude angle data of the thrown object are calculated in a non-contact and high-precision mode.

The invention relates to the field of urban road modeling, in particular to an aerial photography data processing method and system for urban road modeling. The invention discloses an aerial photography data processing system for urban road modeling. The aerial photography data processing system comprises an aerial photography video acquisition module, a road modeling module, a photogrammetry module, a spatial registration module and a rendering synthesis module. According to the invention, on the basis of a spatial calibration mechanism of the original aerial image and the BIM model, redundant processes such as point cloud acquisition, data fusion and manual correction are eliminated, and linear processing from data acquisition to dynamic result output is realized; according to the architecture, the hardware resource dependency and the operation complexity are greatly reduced, and designers are endowed with the capability of completing large-scale scene visualization processing in a conventional engineering environment; according to the method, a transmission chain from original data to decision support is remarkably shortened, and important engineering scheme deduction and dynamic review have unprecedented timeliness.

The invention provides a dynamic change monitoring method and system based on a multi-temporal river channel image, and relates to the technical field of image monitoring, and the method comprises the steps: obtaining a multi-temporal multispectral remote sensing image and an unmanned plane oblique photogrammetry image; identifying a riverway water body boundary and constructing a water area mask; dense point cloud data are generated and cut; generating a balanced riverbed point cloud through density compensation sampling and local curvature constraint; constructing a terrain model to generate a section sequence; calculating hydrodynamic correlation strength to construct an evolution propagation sequence; and recursively calculating the erosion and deposition change rate and performing early warning. According to the invention, high-precision monitoring and early warning of river form changes are realized.

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.

A remote-sensing yield estimation method is described that is applicable to a crop whole growth period and belongs to the field of data processing methods and photogrammetry technologies with prediction purpose. In the present disclosure, in combination with agricultural knowledge of crop yields and multi-source remote-sensing data, with the biomass estimation model of whole growth period, the biomass contribution rate curve and the crop harvest index as basis, a crop yield estimation model of whole growth period with stable spatiotemporal extensibility is constructed. The yield estimation model uses the relative accumulated temperature and the remote-sensing vegetation index as variable inputs. Further, based on genetic algorithm, the parameters of the model are optimized in a case of failing to directly construct the model with data fitting due to less sample points, so as to help solve the problems of poor spatiotemporal mobility of the yield estimation model.

A method is provided for generating a three-dimensional (3D) visually representative model of a vehicle. The method includes receiving images acquired from a number of viewpoints of different sections of the vehicle, and performing photogrammetry on the images to extract a profile of the vehicle. The method includes creating a wireframe mesh or point cloud from the profile, and generating the 3D model of the vehicle. The images are processed to determine areas on a surface of the vehicle in which a defect is detected, and markers are appended onto respective areas of the 3D model that correspond to the areas on the surface of the vehicle such that the defect is appended onto the 3D model. And the method includes generating a display of the 3D model of the vehicle including the markers that indicate the areas on the surface of the vehicle in which the defect is detected.

The invention discloses a large workpiece strain measuring point auxiliary positioning system and method, and the system comprises a professional software and automatic control system, and an industrial photogrammetry system, a car lifting system, a laser projection system and a three-dimensional scanning quantitative analysis system which are connected with the professional software and automatic control system. And a positioning target is arranged on the surface of the large workpiece product. According to the system, strain contact auxiliary lineation and laser guide assembly work of a large workpiece and quantitative analysis work of strain gauge pasting are achieved, the system takes a target arranged on a product as a positioning reference, the outline of a product model is extracted in a photogrammetry mode, the product model and a real object are matched and unified to the same coordinate system, and the product model and the real object are obtained. The position contour of the strain gauge needing to be pasted and auxiliary information are projected to the surface of a product through the laser projection technology, the current pasting position information can be efficiently and accurately reflected, and high-efficiency and high-precision assembly of the strain gauge is facilitated.

Systems and methods for ascertaining a position of an orthopedic element in space comprising: capturing a first and second images of an orthopedic element in different reference frames using a radiographic imaging technique, detecting spatial data defining anatomical landmarks on or in the orthopedic element using a deep learning network, applying a mask to the orthopedic element defined by an anatomical landmark, projecting the spatial data from the first image and the second image to define volume data, applying the deep learning network to the volume data to generate a reconstructed three-dimensional model of the orthopedic element; and mapping the three-dimensional model of the orthopedic element to the spatial data to determine the position of the three-dimensional model of the orthopedic element in three-dimensional space.

The invention belongs to the technical field of glacier identification, and provides a system for monitoring glacier dynamics by an unmanned aerial vehicle low-altitude flight photogrammetry method, which comprises the following steps that: a glacier area unmanned aerial vehicle low-altitude photogrammetry module selects an unmanned aerial vehicle as required, and plans a route and parameters; the image preprocessing module is used for extracting key feature points from each image by using Pi * 4Dcap; fine three-dimensional information, an ortho-image and a glacier digital surface model DSM are obtained through point cloud generation and densification, and glacier dynamic information can be identified by utilizing the glacier digital surface model DSM after correction and interpolation processing are carried out on the three-dimensional information, the ortho-image and the glacier digital surface model DSM; calculating the elevation, volume, speed and mass change of the glacier based on a digital surface model (DSM) of the glacier; the glacier fissure is identified by utilizing the orthoimage and the glacier digital surface model DSM, and the system can comprehensively and accurately monitor the dynamic information of the glacier.

A rock mass informatization model establishment method based on laser point cloud relates to the field of model identification and analysis, and is characterized by comprising the following steps: unmanned aerial vehicle laser data acquisition; establishing an inclination model; re-matching the laser point cloud flight strip; carrying out refined point cloud classification; establishing a triangulation network model; establishing a rock form model; establishing a rock mass information model; establishing a rock mass analysis system; and collapse simulation. The method provided by the embodiment of the invention has the advantages that the unmanned aerial vehicle can be used for carrying the laser radar to carry out close-to-land imitation flight, structures such as collapse, cracks and rockfall of the mountain under the dense forest can be directly measured by using the good vegetation penetrating ability of the laser point cloud, and compared with the original modes such as field investigation and photogrammetry, the method has the advantages that the measurement accuracy is greatly improved. The information obtained by the laser point cloud is more accurate and comprehensive, and the geometric dimension, the steep cliff section shape, the structural surface feature, the lithology, the boundary condition and other features of the dangerous rock mass can be directly confirmed.

The invention discloses a field-ditch-pond extraction method based on unmanned aerial vehicle photogrammetry and deep learning, and belongs to the technical field of remote sensing technology and agricultural informationization, and the method comprises the steps: employing an unmanned aerial vehicle to carry a multispectral camera and an optical lens, and obtaining original image data through an oblique photogrammetry technology; preprocessing the obtained original image data to generate a multispectral image map (DOM) and a digital surface model (DSM); starting from the spectrum, terrain and texture features of a small watershed field-ditch-pond system, a U-net algorithm with a built-in attention mechanism, an image segmentation model supporting zero sample learning, a multi-scale segmentation technology and a multiple extraction framework of a shape feature extraction algorithm are constructed, image segmentation, classification and interpretation are carried out, and a multi-scale image segmentation model is constructed. Fine extraction of the small watershed field-ditch-pond system is realized; the design can improve the extraction precision and efficiency under complex terrains, and is suitable for current small watershed agricultural non-point source pollution migration trajectory simulation and farmland fine management.

The invention provides a waste slag field soil erosion determination method based on a three-dimensional model, and relates to the technical field of engineering construction, and the method comprises the following steps: obtaining an initial terrain image; constructing a three-dimensional vector model of the waste slag field; a plurality of image control points are arranged on the periphery of the waste slag field; installing a plurality of fixed oblique photogrammetry devices with three-axis attitude control; the method comprises the following steps: regularly collecting multi-angle image data of a waste slag field by using an oblique photogrammetry device, obtaining image data of different visual angles, and carrying out encryption matching on the collected multi-angle image data until a preset coordinate resolution requirement is met; processing the matched image data to generate three-dimensional point cloud data, and utilizing the three-dimensional point cloud data to construct a three-dimensional irregular triangulation network model of the waste slag field; calculating elevation change in a preset time interval; adopting a numerical analysis method to extract change data of the waste slag body; and evaluating the stability of the waste slag field according to the change data. According to the invention, high-precision, omnibearing and dynamic monitoring of the waste slag field can be realized.

The invention discloses a space-space-ground-well integrated carbon dioxide sequestration leakage monitoring method and system, and relates to the technical field of carbon dioxide sequestration leakage monitoring, and the method comprises the steps: carrying out the remote sensing measurement of a target region through a synthetic aperture radar and a satellite, and determining a carbon dioxide sequestration leakage monitoring boundary; performing photogrammetry by using an unmanned aerial vehicle, and constructing a three-dimensional real scene model Surveying the target area on site to obtain surveying and mapping data; based on the key monitoring area, an absorption spectrum and earth surface leakage flux are obtained through infrared spectrum monitoring and vorticity monitoring; gravity monitoring data, storage area underground water parameters, carbon dioxide plume distribution conditions and logging sound wave frequency distribution characteristic graphs are obtained through gravity monitoring, underground water monitoring, optical fiber monitoring and sound wave logging monitoring. And through comprehensive analysis, according to a comprehensive analysis result, whether carbon dioxide leaks is judged, and a carbon dioxide sequestration leakage monitoring result is obtained. The accuracy of carbon dioxide sequestration monitoring can be effectively improved.

The invention provides an attitude measurement camera coordinate system calibration method, apparatus and device, and a storage medium, which can be applied to the technical field of measurement calibration. The method comprises the steps that a calibration plate is constructed, a conversion target seat and at least one reflective mark point are arranged on the calibration plate, the conversion target seat is used for placing a cube-corner prism target ball and a photogrammetry target ball, the cube-corner prism target ball and the photogrammetry target ball are the same in diameter, and the calibration plate is placed at different positions in a view field of an attitude measurement camera; the method comprises the following steps: acquiring three-dimensional coordinates of a cube-corner prism target ball by using a laser tracker, replacing a photogrammetric target ball, shooting an image of a calibration plate by using an attitude measurement camera to obtain the three-dimensional coordinates and a plurality of images of the cube-corner prism target ball in a laser tracker coordinate system, and calculating the three-dimensional coordinates of the cube-corner prism target ball according to the three-dimensional coordinates and the plurality of images of the cube-corner prism target ball in the laser tracker coordinate system. And calibrating a coordinate system of the attitude measurement camera. The extraction precision of the two-dimensional image coordinates of the target spot can be improved, and then the calibration precision of the coordinate system is improved.

The invention relates to the field of power system operation and maintenance, in particular to a three-dimensional visualization method applied to a substation operation and maintenance system, which comprises the following steps of: acquiring a three-dimensional model and position information of substation equipment, constructing an integral three-dimensional model of a substation by utilizing technologies such as laser scanning and photogrammetry and combining positioning technologies such as GPS (Global Positioning System) and RTK (Real-Time Kinematic); a sensor is installed on equipment, operation parameters such as voltage, current, temperature and vibration are collected in real time and transmitted to a three-dimensional visualization system through a wireless or wired communication network, association display of real-time data and a three-dimensional model is achieved, and the system provides a three-dimensional view capable of rotating, zooming and translating. The operation state and fault alarm information of the equipment are displayed in real time, and historical data query and alarm log functions are supported. By analyzing real-time and historical data, the system can identify and predict potential faults of the equipment, generate maintenance plans and optimization suggestions, and support remote collaboration and fault handling.

The invention provides a seawall terrain extraction method and system fusing a vehicle-mounted laser point cloud and an inclination model. The method comprises the following steps: forming a seawall range according to a seawall vector diagram and a satellite image; dividing a seawall range into a vehicle-mounted laser radar acquisition range and an unmanned aerial vehicle oblique photogrammetry range; acquiring a vehicle-mounted laser point cloud collected by a vehicle-mounted laser radar, and performing preprocessing and precision optimization on the vehicle-mounted laser point cloud; obtaining oblique photography image data collected by a five-splicing camera carried by the unmanned aerial vehicle, and generating an oblique photography model and an oblique three-dimensional model point cloud; extracting edge line elements and angular point feature points of a common overlapping area in the inclined three-dimensional model point cloud and the vehicle-mounted laser point cloud, and performing point cloud fusion based on the edge line elements and the angular point feature points; filtering the fused point cloud to screen seawall terrain point cloud data; according to seawall terrain point cloud data, resolution-adaptive digital elevation models are constructed for different areas of a seawall, and seawall structure features can be accurately represented.

The invention discloses a target positioning and recognition method for high-precision photogrammetry of a jacket. The target positioning and recognition method for high-precision photogrammetry of the jacket comprises the following steps: obtaining a plurality of jacket images through photogrammetry; drawing a histogram of the image; determining imaging conditions; using a real-time target detection algorithm to coarsely detect a possible circular target area; ellipse detection under different imaging conditions; positioning a circle center; and decoding the coding mark. According to the target positioning and recognition method for high-precision photogrammetry of the jacket, high-precision measurement work of the deepwater ultra-large jacket can be effectively completed through the target positioning and recognition method, and the measurement precision of completion measurement of the deepwater ultra-large jacket is effectively improved.

Systems and methods for generating patient-specific surgical guides comprising: capturing a first and second images of an orthopedic element in different reference frames using a radiographic imaging technique, detecting spatial data defining anatomical landmarks on or in the orthopedic element using a neural network, applying a mask to the orthopedic element defined by an anatomical landmark, projecting the spatial data from the first image and the second image to define volume data, applying the neural network to the volume data to generate a reconstructed three-dimensional (“3D”) model of the orthopedic element; and calculating dimensions for a patient-specific surgical guide configured to abut the orthopedic element.

The invention discloses a slope monitoring and early warning method based on oblique photography and radar technologies. The method comprises the following steps: acquiring three-dimensional point cloud data and surface texture data of a slope; constructing a risk identification model; inputting the three-dimensional point cloud data and the surface texture data into a registration fusion module for registration fusion to obtain three-dimensional image data of the slope; the three-dimensional image data of the side slope are input into an image recognition module for crack recognition, and a crack image is obtained and comprises crack positions, sizes and the number; the crack image is input into a comparison module, and whether risk warning is carried out or not is judged based on a preset threshold value; and further dynamically adjusting the scanning frequency of the synthetic aperture radar through the crack image. According to the method, the three-dimensional point cloud data acquired by the multi-line laser radar and the surface texture data acquired by the oblique photography unmanned aerial vehicle are fused, so that high-precision and comprehensive identification of the slope crack can be realized.

An example embodiment of the present invention provides a method of assessing the condition of a pavement site, comprising: (a) acquiring aerial images of the site from above, for example by an unmanned aerial system (UAS); (b) using photogrammetry tools to generate an orthomosaic that represents the airport pavement surface; (c) using image analysis tools and machine learning methods to determine the location and extent of defects in the pavement; (c) producing an image representation of the site and the defects, where the location and extent of defects are discernible from the image; (d) using software application techniques to store and present defect data and other related information for client-side user access.

The invention relates to a method for determining a position of a rail vehicle, moving on a track, by means of an optical measuring system comprising a stereo camera system and an evaluation device, wherein by means of the stereo camera system an image pair is recorded from a reference point in a lateral environment of the track and wherein by means of photogrammetry the position of the rail vehicle is determined in relation to the reference point. The position of the rail vehicle is additionally detected by means of a radio-based measuring system for real-time locating by means of anchor modules attached to the rail vehicle and by means of transponders attached to several reference points, wherein position data of the two measuring systems are compared by means of a central system unit. In this way, two independent measuring systems are used to generate position data.

The invention relates to the technical field of digital twinborn simulation, in particular to a digital twinborn simulation system for a sleeper maintenance period, which comprises a multi-source data integration module for integrating point cloud data of a laser scanner and a photogrammetric image sequence of an unmanned aerial vehicle, extracting steel rail profile point position coordinates and sleeper position geometric parameters of a sleeper, and generating a digital twinborn simulation result; and generating an integrated structure attribute set. According to the invention, by integrating the point cloud data of the laser scanner and the photogrammetric image sequence of the unmanned aerial vehicle, the space coordinates of the steel rail profile and the geometric parameters of the sleeper are obtained, and a unified space coordinate system is constructed, so that the accuracy and stability of data matching are improved; and the displacement vector and attitude difference between the actually measured data and the digital model are taken as an adjustment basis, so that the adjustment operation of the steel rail node coordinate and the sleeper rotation matrix is more in line with the actual track facility state, the consistency of the simulation geometric structure and the actual track structure is realized, and the credibility of model simulation analysis is improved.

The invention provides a real-time identification and positioning method and device for an all-weather unmanned aerial vehicle in a limited airspace based on deep learning. The real-time identification and positioning method is based on at least two cameras and an infrared sensor which are mounted on a holder; the method comprises the following steps: firstly, ensuring that a limited airspace image is stably captured by utilizing holder control based on adaptive Kalman; then, splicing a plurality of captured images into a complete high-definition panoramic image based on an infrared and optical panoramic fusion technology; the unmanned aerial vehicle target in the high-definition panoramic image is detected and recognized in real time based on target detection; and finally, by adopting an aerial target positioning technology based on photogrammetry, according to the identified position of the unmanned aerial vehicle target in the high-definition panoramic image, and by combining a photogrammetry principle, calculating a specific position coordinate of the unmanned aerial vehicle target in the space, thereby realizing real-time identification and positioning of the unmanned aerial vehicle.

The invention provides an aerial survey unmanned aerial vehicle route planning method and system, and the method mainly comprises four steps: map coordinate conversion, polygon processing, polygon decomposition, and path planning, and through the four steps, the aerial survey unmanned aerial vehicle route planning method employs a full-coverage path planning algorithm. After the boundary of the operation area and the coordinate information of the no-fly area are obtained, the air route is automatically generated to avoid the no-fly area and the path is shortest, so that the method is really applied to aerial photogrammetry operation, the reasonable shortest path can be planned for the operation area in any shape, the operation area cannot fly to the no-fly area, the turning frequency is reduced, and the working efficiency is improved. The phenomenon of repeated flight is avoided, and the operation efficiency of the aerial survey unmanned aerial vehicle is improved.