79 results about "Motion recovery" patented technology

The invention relates to an unmanned aerial vehicle aerial photography sequence image-based slope three-dimension reconstruction method. The method includes the following steps that: feature region matching and feature point pair extraction are performed on un-calibrated unmanned aerial vehicle multi-view aerial photography sequence images through adopting a feature matching-based algorithm; the geometric structure of a slope and the motion parameters of a camera are calculated through adopting bundle adjustment structure from motion and based on disorder matching feature points, and therefore, a sparse slope three-dimensional point cloud model can be obtained; the sparse slope three-dimensional point cloud model is processed through adopting a patch-based multi-view stereo vision algorithm, so that the sparse slope three-dimensional point cloud model can be diffused to a dense slope three-dimensional point cloud model; and the surface mesh of the slope is reconstructed through adopting Poisson reconstruction algorithm, and the texture information of the surface of the slop is mapped onto a mesh model, and therefore, a vivid three-dimensional slope model with high resolution can be constructed. The unmanned aerial vehicle aerial photography sequence image-based slope three-dimension reconstruction method of the invention has the advantages of low cost, flexibility, portability, high imaging resolution, short operating period, suitability for survey of high-risk areas and the like. With the method adopted, the application of low-altitude photogrammetry and computer vision technology to the geological engineering disaster prevention and reduction field can be greatly prompted.

The invention discloses a real human body three-dimensional modeling method specific to personalized virtual fitting. According to the method, a video is used as input data; and several steps of feature matching, key frame selection, three-dimensional point cloud generation, template mapping, and texture mapping and the like are carried out to obtain a human body surface three-dimensional model. Because of the motion recovery structure technology, the reconstruction process is substantially simplified, the burdens of the data collection people and the collected people can be reduced, and the requirements on the instrument and equipment are reduced. Meanwhile, a precise reconstruction result can be obtained. A complete human body surface model is obtained based on template mapping; and thus the method has high robustness on the human body texture information missing and self-shielding. Therefore, only a plurality of control points need to be marked manually before template mapping from the data input to model output and other process is completed automatically. The model that is obtained based on reconstruction can be applied to the game and animation design, movie and television special efficacy, and personalized virtual fit and the like.

The invention discloses a lower-limb motion recovery machine with multiple body positions. Two ends of an electric linear hip pushing rod (29) are respectively articulated with the tail end of a hip rod (18) and an upper thigh rod (22), and the electric linear hip pushing rod (29) drives the hip joint to move; two ends of an electric linear knee pushing rod (30) are respectively articulated with a lower thigh rod (24) and an upper shank rod (27), and the electric linear knee pushing rod (30) drives the knee joint to move; and two ends of an electric linear ankle pushing rod (31) are respectively articulated with a lower shank rod (28) and the front end of a foot rod (21), and the electric linear ankle pushing rod (31) drives the ankle to move. Compared with the prior art, an outer joint assisted motion exoskeleton of the lower-limb motion recovery machine with multiple body positions can simulate the walking motion of the lower limbs of a human so as to drive the lower limbs of a patient to walk so that walking skills of the patient can be improved, or gradually recovered and accurately mastered.

The invention discloses a three-dimensional reconstruction method of a large-scene object. The method comprises the following steps: 1, acquiring a plurality of sequence pictures of the scene object from different visual angles and positions by use of a camera; 2, dividing the sequence pictures into a plurality of units Ni; 3, performing feature detection and matching on three sequence pictures of each unit by use of an SIFT algorithm; 4, initializing a first sequence picture of a unit N1 (i=1), and calculating a basic matrix F and an intrinsic matrix E of the other two sequence pictures; 5, solving camera parameters Ri and Ti and three-dimensional point cloud coordinates Mj of each sequence picture in other units; 6, obtaining seed surface sheets of the scene object; 7, expanding the seed surface sheets; and 8, filtering the seed surface sheets. According to the invention, by use of three-view constraints, mismatch points are effectively removed, an accurate basic matrix is obtained, the reconstruction precision is high, the units do not need coordinate conversion, the calculation complexity is reduced, and through performing dense reconstruction on the basis of a motion recovery structure, obtained point clouds of a three-dimensional model are enabled to be denser.

A method for restoring video human body 3-D movement based on side shadow and tail end node includes picking up side shadow from video, making tail end node detection on side shadow, seeking optimum attitude enabling to explain positions of side shadow and tail end node on the image through analog annealing algorithm and connecting attitude of each frame to form continuous 3-D movement sequence after post-treatment.

The invention discloses a single-lens three-dimensional image reconstruction method based on laser radar point cloud data assistance. The method comprises the steps: acquiring multiple visible light images and laser radar point cloud data of a scanned object; based on the laser radar point cloud data, adopting an incremental motion recovery structure algorithm to carry out three-dimensional reconstruction on the visible light image so as to acquire an image point cloud; and registering the image point cloud and the laser radar point cloud data by adopting a mode of combining rigid transformation and non-rigid transformation to obtain a three-dimensional point cloud model of a scanned object. According to the method, geometric correction is carried out by adding virtual ground control points in the three-dimensional reconstruction process of the image in a mode of searching homonymous points of the image and the laser radar point cloud, so that the distortion condition in the three-dimensional reconstruction process of the image can be reduced; and image point cloud and laser radar point cloud data are registered in a rigid transformation and non-rigid transformation combined mode,the registration precision can be improved, and high-precision three-dimensional point cloud model reconstruction is achieved.

The invention provides an aerial image three-dimensional modeling method and a related product. The method comprises the following steps: obtaining an orthoimage and at least four slanted images, obtaining position information, and importing the position information to the orthoimage and the at least four slanted images; carrying out aerial triangulation on the orthoimage and the at least four slanted images to generate image exterior orientation elements, and recovering postures of the images during shooting; adopting a motion recovery structure for the primarily-treated orthoimage and the primarily-treated at least four slanted images to generate three-dimensional dense point cloud; serving curvature abrupt change points on a mesh of the three-dimensional dense point cloud as feature points, carrying out targeted grouped connection on an unordered feature point set and extracting a characteristic line of the initial position; and carrying out triangle folding simplification and feature preservation processing on the characteristic line of the initial position and outputting and obtaining a three-dimensional model. The technical scheme has the advantages of improving modeling efficiency and stability.

The invention discloses an oil and gas pipeline inspection method based on an unmanned aerial vehicle, and the method comprises the steps: carrying a high-resolution imaging system and a high-precision positioning device by the unmanned aerial vehicle to carry out low-altitude aerial photography, and obtaining continuous oil and gas pipeline images and the position information of the unmanned aerial vehicle; Performing abnormal target detection by adopting a target detection algorithm based on a neural network to obtain an abnormal target; And carrying out abnormal target positioning by adopting an algorithm based on a motion recovery structure. The oil and gas pipeline inspection method provided by the invention is relatively high in intelligent degree, an automatic target detection algorithm is adopted, and target positioning can be realized without adding additional ground control points; The oil and gas pipeline inspection method provided by the invention is relatively high in efficiency; In the abnormal target detection stage, the possible position of an abnormal target is effectively determined through an image segmentation algorithm based on SIFT and Graph Cut, and in the abnormal target positioning stage, under the condition that dense reconstruction, DEM generation and other steps in a traditional algorithm are omitted, high positioning precision can still be obtained.

The invention provides a three-dimensional point cloud model-based landmark building image classifying method. The method comprises the following steps of: selecting a representative image of three-dimensional reconstruction of a landmark building image from a marked landmark building image set to perform visual attention analysis; performing three-dimensional reconstruction on the visual attention area in the acquired landmark building image by utilizing a motion from structure method so as to acquire a three-dimensional point cloud model of the landmark building; projecting the three-dimensional point cloud model into a landmark building image corresponding to the three-dimensional point cloud model by utilizing a projection matrix, identifying a whole image and a local image by means of distribution of projection points, selecting part of the local image contributing to three-dimensional reconstruction from the local image type to perform local reinforcement on the three-dimensional point cloud model, projecting the acquired local reinforced landmark building three-dimensional point cloud model into the landmark building image corresponding to the landmark building three-dimensional point cloud model; and extracting a landmark building area of each landmark building image, establishing a K-dimensional searching tree, and acquiring the type of the landmark building image without any type mark by utilizing the K-dimensional searching tree.

Volume determining method for an object (1), particularly a stock pile, on a construction site, comprising –  moving a mobile camera (8) along a path (10) around the object (1) while orienting the camera (8) repeatedly or continuously, onto the object (1), –  in the course of this, capturing a series of images of the object (1) with the camera (8), the series comprising a plurality of images captured from different points on the path (10) and with different orientations of the camera (8), the series being represented by an image data set collected thereby, –  performing a structure from motion evaluation with a defined algorithm using the series of images and generating a point cloud spatial representation comprising a surface of the object (1) therefrom, –  scaling the spatial representation with help of a known absolute reference regarding scale, the scale being imaged by the camera (8) together with the object (1), –  defining a ground surface for the object (1) and applying it onto the spatial representation and –  calculating and outputting the absolute volume of the object (1) based on the scaled spatial representation and the defined ground surface.

The invention discloses an unmanned aerial vehicle image rapid three-dimensional reconstruction method for a field unknown environment. According to the invention, the method includes using an OpenMPmulti-thread processing mechanism to resize image returned by an unmanned aerial vehicle, sorting the images, extracting feature points in a parallel grid format, obtaining sparse point clouds of allimage clusters through a global motion recovery structure, calculating depth images of the images, and constraining regions of interest through image Mask; and based on a depth map fusion method, obtaining the dense point cloud of each image cluster, and combining the reconstruction results of each cluster to obtain the three-dimensional structure of the whole scene. The method can be realized without depending on complex image acquisition equipment and computer equipment, and the reconstruction speed is greatly improved by using parallel grid type feature extraction; through point cloud partitioning and grid partitioning, the memory pressure is reduced, and the reconstruction speed is increased.

The invention relates to a mobile terminal three-dimensional reconstruction and model restoration method and system, and belongs to the technical field of image processing and three-dimensional reconstruction. The method comprises the following steps: S1, collecting a series of image data of a modeling object according to a specified angle, and enabling a camera to focus on the modeling object tofuzzify the background in the process; S2, extracting image feature points by using scale invariant feature transform (SIFT), fusing the feature points of every two images, and maximizing the resolution of the images when the feature points are extracted; S3, completing sparse reconstruction by using a motion recovery structure SFM; S4, completing dense reconstruction by using a stereoscopic vision method MVS; during dense reconstruction, the minimum pixel point threshold value is reduced, so that the effective point cloud is increased; S5, finishing point cloud modeling by using a Poisson reconstruction method PSR; during Poisson reconstruction, shear elements are reduced, so that the effective surface is increased; S6, topology reconstruction is carried out; S7, geometric correction; andS8, the model is displayed, and 3D printing or 3D engraving is conducted.

The invention discloses an underwater scene reconstruction method based on motion recovery, and a storage medium. The reconstruction method comprises: introducing an improved motion recovery algorithm, extracting a motion matrix, establishing a mutual connection between video images, and after completing redundant image culling, performing feature point matching and point cloud generation in two steps: firstly performing feature point matching on the binocular image, generating patches based on the matched feature points in order to obtain more dense point cloud data; then spreading the patches to all angles of view, to complete the reconstruction of the scene model, and finally performing the color correction of on point cloud model according to the imaging characteristics of the underwater scene. The invention may still achieve better reconstruction results when only a few input images are obtained, has relatively good efficiency and precision, and at the same time certainly improvesthe accuracy and robustness of the reconstruction scene.

The invention provides a lower limb lifting motion recovery device which comprises a rack and a plurality of lower limb lifts. The lower limb lifts are arranged on the rack and independently ranked on a same line at intervals, the front-back position of at least one lower limb lift can be adjusted, each lower limn lift comprises a lifting transmission box arranged in the rack, a limb supporting rod which can rise and fall relative to the lifting transmission box, and a limb supporting table rotatably connected to the limb supporting rod, and limb dies matched with the corresponding parts of the human body are detachably arranged on the limb supporting tables. A recovery treatment control system for controlling the lower limb lifts to be mutually matched to rise and fall to make supported lower limbs finish limb rehabilitation excise is arranged inside the rack. The lower limb lifting motion recovery device can lift the lower limbs of the human body and can simulate the motion state of the lower limbs of the human body to effectively recover the limb function.

The invention relates to a self-splicing surface point cloud measurement method without active visual marking. The method is characterized in that a camera and a projector can independently and freelymove to obtain a series of modulated structured light images, the images jointly cover the whole surface to be measured, the images are decoded to obtain the coded information, dense pixel matching is realized according to the coding information in the series of modulation structured light images, meanwhile, spatial geometric constraints of the images under different poses are established, then,under the framework of the motion recovery structure, global poses of the camera and the projector corresponding to each image are calculated and optimized, and space coordinates of three-dimensionalpoints are reconstructed, and lastly, point cloud data of the whole surface to be measured in a unified world coordinate system. The method is advantaged in that marking points do not need to be arranged in advance, an independent point cloud splicing post-processing algorithm is not needed, meanwhile, operation is flexible, and the method can be suitable for accurate measurement of objects of different sizes and shapes.

The invention discloses an aircraft position determination method based on a motion recovery structure. The method is characterized in that an imaging device is used to continuously image the terrainunder a track to obtain a motion sequence image; and then a real-time three-dimensional topographic map is restored based on the motion sequence image and spatial three-dimensional coordinates of thepoints on the real-time three-dimensional topographic map under an attitude coordinate system of an aircraft body are obtained. The spatial three-dimensional coordinates of the points on the real-timethree-dimensional topographic map under the attitude coordinate system of the aircraft body are transformed to a parallel coordinate system of the aircraft. The spatial three-dimensional coordinatesof the points on the real-time three-dimensional topographic map under the parallel coordinate system of the aircraft can be converted to a ground reference terrain coordinate system, and finally theposition of the aircraft under the ground reference terrain coordinate system is solved inversely. The aircraft position determination method can accurately measure the position of the aircraft at lowcost and low energy consumption.

The invention provides an unmanned aerial vehicle aerial photography modeling method based on a BIM technology, and the method comprises the following specific implementation steps: 1, carrying out the aerial photography of an unmanned aerial vehicle, collecting the related information of an on-site construction drawing, and obtaining the landform and on-site conditions of a project based on a motion recovery structure algorithm and scale invariant feature conversion; 2, completing later-stage GIS data processing of the aerial survey by adopting ContextCapture; 3, a local area network is built, and GIS data are processed in a cluster mode; Step 4, importing the model raw material data into revit software to generate a three-dimensional model; and 5, arranging on-site temporary constructionand planning construction routes and specific construction schemes by using the geomorphic model generated by revit software in combination with the design drawing. Aerial photography modeling of theunmanned aerial vehicle is well utilized based on the BIM technology, rapid and accurate modeling is achieved, the modeling mode is more convenient, the model culvert surface is wider, daily aerial photography of the unmanned aerial vehicle is achieved, the modeling progress is dynamically followed, and construction is guided.

The invention relates to the field of oblique photography three-dimensional reconstruction of unmanned aerial vehicles, and discloses an oblique photography three-dimensional reconstruction matching method, which comprises the steps of extracting an image position and a pose feature component; extracting an image color feature component; extracting texture feature components; standardizing the three components, and performing combining to obtain a fusion feature vector; constructing a hash function to map the obtained fusion feature vector; and further calculating the Euclidean distance, performing sorting to form a to-be-matched image set, and then selecting a single image matching object from the to-be-matched image set in the structure motion recovery process. Compared with the prior art, POS information and color texture information of an unmanned aerial vehicle image are fused; the images before reconstruction are clustered according to the characteristics of the unmanned aerial vehicle images, the global matching process of a traditional reconstruction algorithm is avoided, the efficiency in oblique photography image three-dimensional reconstruction is remarkably improved, and the reconstruction dense point cloud can keep good precision while the reconstruction efficiency is improved.

The invention discloses a binocular vision camera hardware system, and a three-dimensional scene reconstruction system and method. The three-dimensional scene reconstruction system comprises an ECU, the binocular vision camera hardware system and a GPS module; when the ECU determines that the distance between a vehicle and the front turning position reaches the preset distance according to navigation information sent back by the GPS module, the ECU controls binocular vision cameras to synchronously rotate in a reciprocating mode in the preset rotating range to collect image data in a 180-degree view field in front of the vehicle, and conducts three-dimensional scene reconstruction on the image data collected by the left camera and the right camera in the 180-degree view field in front of the vehicle on the basis of a motion recovery structure principle and an instantaneous positioning and map construction principle, and thus a three-dimensional scene reconstruction image in the 180-degree view angle in front of the vehicle is obtained. Only one set of binocular vision camera with the one-dimensional rotating function is adopted to realize image collecting in the 180-degree view angle in front of the vehicle, and thus the hardware cost for three-dimensional scene reconstruction is reduced.

The invention discloses a rapid logging method for high cut slope geology based on a three-dimensional point cloud reconstruction technology. The method comprises the following steps: 1, acquiring data of the unmanned aerial vehicle; 2, carrying out a motion recovery structure process; step 3, post-processing the point cloud data; and 4, identifying and extracting a structural surface. According to the invention, the problems of low working efficiency and high cost of a high-precision three-dimensional laser scanner in the traditional geological logging are solved; the method has the advantages of low cost, easiness in operation, good effect and high efficiency.

The invention provides an incremental multi-view three-dimensional reconstruction method, belongs to the technical field of computer vision, and solves the problem of utilization of reconstructed model information in a multi-view three-dimensional reconstruction process. The method comprises the following steps: 1, obtaining a three-dimensional reconstruction model by utilizing a motion recovery structure method, and respectively storing an image path, an image camera matrix and reconstructed three-dimensional point information into a memory; 2, reading a new image and a three-dimensional reconstruction model, determining an initial image pair according to an image feature matching relation and a two-dimensional three-dimensional mapping relation, and reconstructing a three-dimensional point cloud; 3, newly adding one to-be-reconstructed image each time, and reconstructing the to-be-reconstructed newly added image until all the images are reconstructed; and 4, carrying out multi-view stereoscopic vision dense reconstruction based on a patch on the reconstructed sparse point cloud model to complete multi-view three-dimensional reconstruction. The method is high in applicability, andthe processes of manual image set screening and sorting and three-dimensional registration are simplified.

The invention discloses a real scene three-dimensional semantic reconstruction method and device based on deep learning and a storage medium, relates to the technical field of remote sensing surveying and mapping geographic information, and solves the problem of inaccurate multi-scene labeling in the prior art. The method comprises: obtaining anaerial image; carrying out semantic segmentation on the aerial image, and determining a pixel probability distribution diagram; performing motion structure recovery on the aerial image, and determining a camera pose of the aerial image; performing depth estimation on the aerial image, and determining a depth map of the aerial image; and performing semantic fusion on the pixel probability distribution map, the camera pose and the depth map to determine a three-dimensional semantic model. Thus, high-precision segmentation is realized under the conditions of more scene objects, serious stacking and the like is realized; and in a large-scale scene, the performance of the depth estimation network is not affected, stable and accurate estimation can be carried out in various scenes, and compared with other traditional three-dimensional reconstruction algorithms, the semantic three-dimensional reconstruction algorithm constructed by the invention has the advantage that the calculation speed is increased.

The invention discloses a rapid image splicing method based on optimized three-dimensional reconstruction, and the method comprises the steps: constructing dense point clouds of a photographing regionthrough employing a motion recovery structure and a multi-view stereo technology, and achieving the splicing of an image through the dense point clouds; optimized feature descriptors are adopted in image feature point extraction to perform optimization adjustment, and when error accumulation is eliminated, an optimization strategy of how to select a next optimal view after initialization is completed is proposed, so that the accuracy of point cloud generation is ensured, and the possibility of failure of a bundle adjustment method is reduced.

The invention provides a bone joint motion rehabilitation assistance device and a method. The device comprises arm fixing plates, rotation rings, first transmission rods, rotation unit housings, second transmission rods, rotation buttons, control slide plates, and screws, wherein the arm fixing plates are cylindrical; the rotation rings are connected with the arm fixing plates; one end of each first transmission rod is fixedly connected with each rotation ring one end of each rotation unit housing is fixedly connected with the other end of each first transmission rod; one end of each second transmission rod is connected with the other end of each rotation unit housing; the rotation buttons are arranged on the outer sides of the rotation unit housings; and the control slide plates are arranged on the rotation buttons. The device solves the technical problems of a poor operation effect and slow recovery due to nerve damage, amyotrophy, synarthrophysis, stiffness and the like caused by postoperative motion incapability of a patient, and achieves technical effects of enlarging a motion range of the patient, assisting patient in bone joint motion recovery and accelerating a recovery rate.

The invention discloses a motion recovery device, and belongs to the field of medical instruments. The device comprises a shell and a water bag laid on the inner wall of the shell, wherein two end parts of the shell in the axial direction are opened; the water bag is provided with a water inlet and a water outlet; an inflation air bag is arranged between the water bag and the shell; and an inflation and deflation port is arranged on the inflation air bag. The device is simple in structure and reasonable in design, can effectively improve portability and popularization degree, and has a better use effect.

The invention discloses a neurology clinical treatment device. The neurology clinical treatment device comprises two symmetrically distributed mobile support mechanisms, a buffer support mechanism isfixed between the tops of rear ends of the two mobile support mechanisms, a lower limb rehabilitation mechanism is installed at the top of the buffer support mechanism, two moving support mechanisms are horizontally fixed with a connecting beam, and an upper limb rehabilitation mechanism is installed at the top of the mobile support mechanism. The device can recover the limbs of a user at the sametime through the scientific and reasonable structural design, and can effectively exercise the rehabilitation of the limbs of the user through the design of the lower limb rehabilitation mechanism and the upper limb rehabilitation mechanism, the design of the buffer support mechanism avoids the impact of the user during a motion recovery process, the recovery speed of the treatment is accelerated, the ingenious design of the mobile support mechanism allows the user to freely fix the device while using the device outdoors, the personal safety of the user is ensured, and the device has good practical and promotional values.

The invention discloses a coal inventory system based on vision, which comprises a data acquisition module and an image processing module, and is characterized in that the data acquisition module is connected with the image processing module; the data acquisition module is used for receiving image information of a coal storage yard and POS data information of an unmanned aerial vehicle acquired bythe unmanned aerial vehicle, and sending image information and POS data information of the unmanned aerial vehicle to the image processing module; the image processing module is used for calculatingparameters of a camera based on a motion recovery structure algorithm according to the image information and POS data information of the unmanned aerial vehicle, constructing a three-dimensional sparse point cloud model according to the parameters, and reconstructing a dense point cloud model according to the three-dimensional sparse point cloud model;constructing a three-dimensional model of thecoal yard based on a three-dimensional reconstruction algorithm and texture mapping according to the dense point cloud model and carrying out integration on a selected area in the three-dimensional model to calculate the volume of the coal pile, and calculating the weight of the coal pile according to the coal type of the selected area and the corresponding density.

The invention relates to the technical field of geological information, in particular to a geological outcrop rapid three-dimensional reconstruction method based on a motion recovery structure, whichcomprises the following steps: arranging control points and measuring rods for geological outcrop and geological phenomena, shooting at least more than three pictures for each geological outcrop surface, and restoring the size of a real three-dimensional geological outcrop model; after corresponding proportional constraint information is added, optimizing and adjusting the attitude position of thecamera by adopting light beam adjustment; after the accurate sparse point cloud is obtained, using an MVS algorithm to construct the dense three-dimensional point cloud of the geological outcrop; after the dense point cloud is obtained, constructing a point cloud triangulation network through Poisson reconstruction, and obtaining a geological three-dimensional model; attaching corresponding geological outcrop texture information to the three-dimensional model, and restoring a real geological three-dimensional model landscape. The three-dimensional model generated by the method can be used forgeological structure extraction, attitude element measurement and formation unit division, and a highly realistic geological three-dimensional model can be generated by combining a 3d printing technology.

The invention provides a method for monitoring and evaluating a river by using unmanned aerial vehicle surveying and mapping. The method comprises the following steps: acquiring image data by using anunmanned aerial vehicle; reconstructing the image data by using a motion recovery shape algorithm to construct 3D topographic information; utilizing a Vextractor program to speculate the basic shapeof the river streamline on the 3D topographic information according to the image data, and fitting the basic shape into a river curvature index of the main river channel section; calculating an ortho-image spectral index by using an RGB ortho-image measurement program to obtain river quantitative and qualitative information; and evaluating the physical environment of the river according to the curvature index and the quantitative and qualitative information of the river. The invention provides a river monitoring and evaluating method. The unmannedaerial vehicle is taken as the infrastructure,a motion recovery shape algorithm, a Vextracto program and an RGB ortho-image measurement program are utilized to track the eutrophication process in the large river and reflect the change process ofeutrophication and vegetation overgrowth, and the method has very important application value for long-term monitoring and ecological restoration of the large river.

The invention relates to an incremental unmanned aerial vehicle aerial photography overlapping degree detection method and system. The overlapping degree detection method comprises the following steps: acquiring exterior orientation elements of all images in a shooting area of an unmanned aerial vehicle; constructing an image connection graph according to the exterior orientation elements; extracting feature points of all the images; matching the image pair according to the feature points, and determining multi-view matching points; obtaining a camera internal reference matrix, and establishing an object space initial model according to the camera internal reference matrix; iteratively optimizing the object space initial model by using an incremental motion recovery structure method SFM, and determining an object space reconstruction model; determining a projection image according to the multi-view matching point and the object space reconstruction model; and detecting an image courseoverlapping degree and a lateral overlapping degree according to the spatial overlapping relationship between the projection images of the projection images. By adopting the overlapping degree detection method or system provided by the invention, the overlapping degree detection efficiency and the accuracy of the detection result can be improved.