2666 results about "Cartography" patented technology

The invention discloses a dynamic three-dimensional reconstruction method based on incremental updating, which belongs to the field of image data processing, and comprises the following steps: acquiring a forestry scene multi-view image to be reconstructed to form an initial data set D0; constructing an initial three-dimensional scene model of the forestry scene based on D0 and 3DGS methods; monitoring a forestry scene to construct an incremental data set Dt of the tth change; during each incremental learning, the previous incremental model is divided into a change area and a non-change area, and the incremental model of the tth incremental learning is obtained by optimizing the change area and the non-change area and constructing a new scene model and is used for image rendering. According to the method, full-scene reconstruction is avoided, and the accuracy of the three-dimensional model can be ensured while the efficiency of three-dimensional reconstruction in a dynamic environment is remarkably improved. And the scene can be updated only by adding a small number of view angle images, so that the cost and time of data acquisition are greatly reduced, and the method is particularly suitable for large-scale monitoring of forestry and the like and scenes needing long-term monitoring and real-time updating.

A system for providing an extended reality environment that incorporates real-world event data into 3D models representative of the real-world event within the extended reality environment includes an XR processing unit configured to dynamically download 3D hole models of the course, receive real-world live shot data of shots taken on the holes during a golf tournament; map the shot data to the 3D hole models; and cause a spatial computing device to render hole views and immersive views comprising the mapped shot data rendered directly on the 3D hole models in real-time in an interactive extended reality environment. The mapped shot data includes shot trails representative of the shots taken on the golf course, The hole views and immersive views may utilize the same source file.

The invention discloses an event camera-assisted multi-modal vehicle-mounted three-dimensional occupancy prediction method, which comprises the following steps of: acquiring continuously acquired laser radar point cloud data, images, events and IMU measurement data, performing synchronization of spatial dimensions and time dimensions on various data, and determining the occupancy of a vehicle-mounted vehicle on the basis of the synchronized laser radar point cloud data and IMU measurement data, so as to predict the occupancy of the vehicle-mounted vehicle-mounted vehicle-mounted occupancy of the vehicle-mounted vehicle-mounted vehicle-mounted vehicle-mounted vehicle-mounted vehicle-mounted image. Dense point cloud data is obtained; performing space-time alignment on the dense point cloud, the image and the event, performing semantic annotation on the image after the space-time alignment, performing dynamic and static separation on the dense point cloud after the space-time alignment through cross-modal semantic projection, and performing static scene optimization and dynamic scene fusion to obtain an occupied voxel true value; training an occupancy prediction model based on the laser radar point cloud data and the occupied voxel truth value; and acquiring laser radar point cloud data and image data of a scene and event data in image exposure time, and realizing three-dimensional occupation prediction by using the trained occupation prediction model.

The invention relates to a three-dimensional live-action model generation method for city updating. The method comprises the following steps: collecting multi-source city image information, and obtaining semantic data according to the multi-source city image information; performing city modeling visualization according to the multi-source city image information to generate a city model; and matching the semantic data with the city model to obtain a three-dimensional real scene model containing the semantic data. According to the method, city information can be obtained more comprehensively by performing total factor accurate collection through a multi-source three-dimensional monitoring technology, the accuracy of a real scene model is improved, semantic data is matched with a city model, a three-dimensional real scene model containing the semantic data is obtained, multiple materials and textures of the model are combined, and the accuracy of the real scene model is improved. And the model is lightened, so that the purpose of reducing the resource loading time is achieved.

The invention discloses a cultural relic handicraft three-dimensional reconstruction method based on multiple views and deep learning, and relates to the technical field of cultural relic handicraft three-dimensional reconstruction methods, and the method comprises the steps: carrying out the image collection of cultural relic handicrafts through employing a multi-view shooting method, and obtaining a structured image data set; performing feature matching and camera parameter estimation on the obtained multi-view image set by adopting a sparse reconstruction method to obtain camera internal parameters, external parameters and sparse point cloud data; performing fine processing on the obtained sparse point cloud data by adopting a dense reconstruction method to obtain a 3D dense point cloud model with a texture map; analyzing the obtained 3D dense point cloud model by adopting a depth map generation method to obtain a depth map and a rendering image corresponding to each image; image acquisition is performed on the cultural relic handicraft by adopting a multi-view shooting method, so that information such as geometric shapes and texture details of the cultural relic handicraft is comprehensively captured, and the problem of information loss caused by a single view angle is effectively solved.

Techniques are provided comprising receiving map data and determining a first polygon representing a first traversable surface and a second polygon representing a second traversable surface. The first polygon may include a first portion that overlaps with a second portion of the second polygon. The techniques may determine, based at least in part on elevation information associated with the first traversable surface and the second traversable surface, respective elevation layers associated with the first polygon and the second polygon. It may be determined whether to merge the first polygon and the second polygon based at least in part on whether the first polygon is associated with a same elevation layer as the second polygon. Based at least in part on determining whether to merge the first and second polygons, an updated map may be determined.

The invention discloses a highly dense broken ice image segmentation method based on an iteration MGAC and an SAM model, and the method comprises the steps: carrying out the sea ice instance segmentation of a preprocessing image based on the SAM model, and obtaining a sea ice mask image corresponding to the preprocessing image; according to the binary image and the sea ice mask image, obtaining an initial sea ice residual region image which is not identified by the SAM model; obtaining initial sea ice residual region images under different gray threshold values to obtain an initial seed mask graph; taking the initial sea ice residual region image and the initial seed mask image as inputs of a preset MGAC contour model, and obtaining an MGAC sea ice recognition result based on a multi-round iteration partitioning mechanism; and performing union operation on the MGAC sea ice identification result and the sea ice mask image to obtain a crushed ice segmentation mask result. The method solves the problem that the existing method is insufficient in structure extraction precision and boundary integrity of the dense broken ice area.

Embodiments of the present disclosure provide a three-dimensional scene reconstruction method and apparatus, a device, a medium, and a program product. The three-dimensional scene reconstruction method comprises: acquiring a scene image collected for a three-dimensional scene; on the basis of the scene image, determining sparse point cloud data and camera parameter information corresponding to the scene image; performing model initialization on the basis of the sparse point cloud data to obtain a current three-dimensional data model; performing rendering on the basis of the camera parameter information and the current three-dimensional data model to obtain a current color map, a current depth map and a current normal map from the perspective of the scene image, and determining a pseudo normal map from the perspective of the scene image on the basis of the current depth map; and on the basis of the current color map, the current normal map, the pseudo normal map, and an actual color map, training the current three-dimensional data model to obtain a trained target three-dimensional data model. By means of the technical solution provided by the embodiments of the present disclosure, higher-quality automatic reconstruction of three-dimensional scenes can be achieved, reducing reconstruction costs, and improving the level of detail and rendering quality of scene models.

The invention discloses an ideological and political large-scale course teaching attention assessment data acquisition method based on sight tracking. The method comprises the following steps: S1, high-definition large-scene eye movement tracking photographing equipment captures eye images of students in a course teaching process in real time through an infrared camera; s2, performing pupil area detection and pupil center fitting on the eye image to obtain sight tracking data; s3, performing gaze hotspot analysis and gaze duration statistics according to the sight tracking data to quantify attention distribution and change trend of the students and visually display the attention distribution and change trend; and S4, generating a teaching quality evaluation report and teaching optimization suggestions according to the gazing hotspot analysis and gazing duration statistical results. The classroom teaching effect can be objectively evaluated in real time, subjective evaluation errors are reduced, the accuracy and efficiency of teaching feedback are improved, the method is suitable for various scenes such as traditional classrooms, online education and experiment teaching, and the method has the industrial application prospect of education digital transformation.

A computer-vision system or engine that (a) generates from a pixel stream a digital representation of a person and (b) determines attributes or characteristics of the person from that digital representation and (c) based on those attributes or characteristics, outputs data to a cloud-based analytics system that enables that analytics system to identify and also to authenticate the person. The attributes or characteristics of the person include their pose, and the system or engine analyses that pose to extract a facial image from a video stream that is the best facial image for use by the cloud-based analytics system to identify and authenticate the person. The computer-vision system or engine outputs the facial image to the cloud-based analytics system, but does not output the full-frame real-time video to the cloud-based analytics system.

The invention relates to the technical field of virtual reality, in particular to a garden landscape digital display and interaction system, hand track depth difference is extracted to construct a gradient path, a facade center point is combined to calculate an orientation included angle, jump calibration projection is analyzed, a leaf surface number is recognized, and an offset adjustment orientation is calculated according to a normal and an illumination included angle. And constructing a similar matrix recombination frame sequence scene, and counting an interaction picture presented by a hotspot coverage combination path access terminal. Visual inertia synchronization is realized by quantifying the depth difference and direction of a hand track, generating nodes based on a gradient threshold, smoothing a path, combining sudden change of an included angle between the nodes and a building center vector and identifying a visual angle switching area, the orientation is adjusted by cosine offset of a leaf surface normal and an illumination included angle, and the light and shadow continuity is improved through matrix reorganization mapping. The high-frequency interaction area is divided by combining the hotspot coverage frequency, and the response efficiency is improved.

The invention discloses a cultural relic three-dimensional dynamic scene display system based on a virtual-real fusion technology, and relates to the technical field of mixed reality, and the system comprises a data collection module which obtains original signals of a to-be-displayed cultural relic and a surrounding environment, and generates an environment feature vector and an environment fusion index; the twinborn simulation module is used for generating health state feature vectors of the cultural relics in combination with finite element grids and carrying out prediction simulation on the deterioration state of cultural relic materials; the model creating module is used for creating a three-tense model resource package and generating time axis metadata by adopting a vertex interpolation and mapping mixing technology; the story layout module is used for constructing an environment event mapping rule base, obtaining a ranked trigger event list through priority ranking, and generating a scene script sequence; according to the method, the health state and the degradation process of the cultural relics under different environmental conditions can be dynamically reflected, and three-dimensional scene display changing along with time evolution is provided.

According to an embodiment, a method for target tracking comprises: determining a plurality of local target trajectories having local target identifications based on a plurality of current frames at a current timing provided by a plurality of cameras; updating a first feature bank including a sub-tracklet feature of a recent sub-tracklet of each local target trajectory and a second feature bank including a sub-tracklet feature of an early sub-tracklet of each local target trajectory based on the plurality of local target trajectories; and performing, in a case where the current timing satisfies a time requirement for a predetermined clustering period, operations of: determining a plurality of current anchors having corresponding current cluster appearance features by clustering features in the union of the updated first feature bank and the updated second feature bank; and determining a global target identification of a detected target based on the plurality of current anchors.

The invention provides a crop population three-dimensional reconstruction and organ phenotypic character analysis method, and relates to the field of three-dimensional reconstruction, and the method comprises the steps: collecting cotton envelope image data, carrying out the data preprocessing, and carrying out the motion recovery processing and Gaussian sputtering of the cotton envelope image data, the method comprises the following steps of: preprocessing a group cotton point cloud, removing a ground point cloud, obtaining a complete cotton group point cloud model, segmenting a cotton individual point cloud model and a corresponding organ point cloud model from the complete cotton group point cloud model, automatically analyzing cotton key phenotypic characters, and performing correlation analysis. According to the method, a cotton original habitat three-dimensional point cloud model is constructed based on mobile visual equipment, and key characters such as cotyledon node height, plant height and leaf area can be automatically analyzed, so that the problems that phenotypic character extraction in the prior art is high in cost, low in flux, easy to make mistakes, inconsistent in standard, generally destructive, labor-consuming, time-consuming and the like are solved.

Techniques are discussed herein for detecting and resolving disparities between sensor data perceived by sensor-based systems operating in an environment and corresponding map data of the environment. Sensor data may be captured by a vehicle or other sensor system operating in an environment, including representations of objects at various locations in the environment. The object representations may be used to determine disparities between the sensor data and map data associated with the same locations. Such disparities may be caused by, for example, physical changes in the environment, map data changes, and / or localization errors of the sensor system. The techniques discussed herein further include analyzing the map data and sensor data to determine causes associated with the disparities, and resolving the disparities by updating the map data and / or transmitting updated sensor configuration data to sensor systems in the environment.

An example method includes receiving a first plurality of coordinate measurement points capturing a portion of an environment and a reference object within the environment, the first plurality of coordinate measurement points defining at least a portion of a first point cloud. The method further includes receiving a second plurality of coordinate measurement points from a position other than the at least one aerial position, the second plurality of coordinate measurement points capturing at least some of the portion of the environment and the reference object within the environment, the second plurality of coordinate measurement points defining at least a portion of a second point cloud. The method further includes aligning the first point cloud and the second point cloud based at least in part on the reference object captured in the first point cloud and the reference object captured the second point cloud to generate a combined point cloud.

A method and an apparatus for constructing hierarchical semantic map based on deep-learning based perception, a server, a storage medium are provided. The method includes: obtaining 3D point cloud data, scene images and motion state data; projecting 3D point cloud data onto an image plane to obtain a depth image; performing a point cloud registration and a pose prediction on the 3D point cloud data and the motion state data to obtain an odometer pose; generating a point cloud map according to the 3D point cloud data and the odometer pose of multi-sensor system; based on the depth image and the odometer pose of the multi-sensor system, performing an external ellipse fitting process on each semantic region in the depth image to obtain an object-enveloped map for respective object images; fusing the coordinately aligned point cloud map and object-enveloped map into a semantic map.

Described is a system for generation location visualization on a map interface by identifying a current location of a user that is initiating an interaction function of an interaction client; identifying a map corresponding to the current location of the user; identifying one or more map tiles associated with the map; receiving historical location data of the user that is associated with the current location of the user; converting the historical location data into an overall polygon that is comprised of a plurality of polygons based on the identified one or more map tiles; and displaying the map with the plurality of polygons on a user interface.

The invention provides a foundation data processing method and system based on three-dimensional point clouds, and relates to the technical field of foundation data processing, and the method comprises the steps: determining a plurality of divided regions of a foundation based on three-dimensional point cloud data before foundation excavation; determining the cross section shot video of each divided area based on the plurality of divided areas of the foundation and the cross section shot video in the foundation excavation process; generating a simulation three-dimensional foundation image of each divided area and mining information of each divided area; determining an earthwork correction coefficient of each divided area based on the simulation three-dimensional foundation image of each divided area and the mining information of each divided area; and determining all corrected earthwork result data based on the estimated earthwork data of each divided area and the correction coefficient of each divided area. The method can accurately determine earthwork data of foundation excavation.

A method for processing sensor data, wherein the sensor data are present as a point cloud of individual points. The points are projected into at least two rasters with different resolutions. Points from a subregion of the point cloud are projected into a first raster with higher resolution and further points of the point cloud are projected into a second raster with lower resolution. Attributes from the first raster are compressed and arranged in the second raster before the attributes from the second raster are compressed.

The invention discloses a ground element labeling method and device, equipment and a storage medium, and the method comprises the steps: determining time sequence data corresponding to a target scene, and constructing three-dimensional point cloud data of the target scene based on the time sequence data; based on the three-dimensional point cloud data, determining a bird's-eye view and an elevation map corresponding to the three-dimensional point cloud data, and displaying the bird's-eye view on a user interface; in response to the detected labeling operation for the ground elements in the aerial view, determining first labeling information of the ground elements; and determining a labeling result of the ground element based on the first labeling information and the elevation map. According to the technical scheme, the three-dimensional point cloud data of the target scene is constructed, and the aerial view and the elevation map are determined based on the three-dimensional point cloud data, so that semi-automatic manual labeling is performed at the BEV perspective, and meanwhile, the 3D labeling result of the ground element is obtained in combination with the elevation map, so that the high-quality ground element labeling true value can be conveniently and quickly obtained.

In one aspect, a grid map construction method includes: acquiring a point cloud of a target scene in the current field of view; according to the point cloud in the current field of view, constructing an occupation grid map and a height grid map corresponding to each other in the current field of view; and then updating a target grid map of the target scene according to a point cloud occupation probability value of each grid in the occupation grid map and a point cloud height value of each grid in the height grid map in the current field of view.

An EVPN network device may advertise an EVPN IMET (type-3) route in a corresponding message to one or more peer EVPN network devices. The EVPN IMET route advertisement message may include an E-tree extended community indicating a leaf or root designation of a locally attached site at the advertising EVPN network device. The inclusion of the E-tree extended community in the EVPN IMET route advertisement message may provide desired traffic handling for implementing an EVPN E-tree service such as handling of BUM traffic.

The invention discloses a court area identification method and device and a storage medium, and relates to the technical field of data processing. According to the method, the depth map and the RGB map of the court acquired by the image acquisition device are acquired, the point cloud data are generated based on the depth map, the point cloud fluctuation amplitude corresponding to the court is determined according to the point cloud data, then the color distribution characteristics and the texture distribution characteristics of the court are determined based on the RGB map, and finally, the color distribution characteristics and the texture distribution characteristics of the court are determined. The area type of the court is determined based on the color distribution characteristics and the texture distribution characteristics of the court and the point cloud fluctuation amplitude corresponding to the court, so that court area identification is more comprehensive and accurate, and the risk that a golf cart enters a forbidden area by mistake is reduced.

The invention discloses a high arch dam global deformation analysis method and system fusing InSAR and measuring point data, particularly relates to the technical field of radar interference deformation monitoring, and is used for solving the problem of inaccurate shielding failure compensation. According to the method, data stability is guaranteed by obtaining InSAR image data and extracting sight line direction displacement in combination with coherence indexes, a key measuring point deformation sequence is collected, an InSAR result is calibrated based on stable reference points, data consistency is improved, a projection correction coefficient is constructed by using a dam body three-dimensional structure model, the sight line displacement is inversely solved into structural normal displacement, and the accuracy of the dam body three-dimensional structure model is improved. Obtaining an initial deformation value of the real structure meaning; according to the method, a spatial coupling map of measuring points and InSAR pixels is constructed for a shielding failure area, deformation compensation of the failure area is completed based on an edge weight, finally the deformation compensation result is remapped to a three-dimensional structure model, measuring point data restoration is performed on a high arch dam, and structural plane-level deformation visualization and trend analysis are realized more quickly and more accurately.

The invention discloses a data processing method for grassland bearing capacity dynamic evaluation and grazing planning, and belongs to the technical field of grassland ecological management, animal husbandry production informatization and data intelligent decision making. Aiming at the technical problems that a traditional static evaluation method neglects grassland productivity dynamic change and a grazing feedback effect, so that the resource utilization efficiency is low and grassland degradation is easily caused, the method dynamically predicts grassland bearing capacity and optimizes a grazing plan through iterative circulation, recursive calculation is carried out in combination with meteorological data and grazing consumption, and the grassland bearing capacity is evaluated. Collaborative optimization of the bearing capacity threshold value and the grazing plan is achieved, and rolling updating is supported. The method can be used for generating a scientific and dynamic grazing scheme, and the utilization efficiency and ecological sustainability of grassland resources are improved.

The invention provides a plant classification labeling method. The method comprises the following steps: S1, acquiring an orthoimage of a target area through an unmanned aerial vehicle, and segmenting to generate plant pattern spots; s2, superposing the orthoimage and the base map of the electronic map, and establishing a composite coordinate system; s3, displaying the superposed map on the mobile terminal, and receiving a marking instruction of a user on the pattern spots; when the user cannot identify the plant type, calling a plant identification API to classify the plant image uploaded by the user, and associating the result to the corresponding plant pattern spot; s4, storing the labeled plant data to a database, and supporting statistics and management of the vegetation types, number and distribution of the target area through a geofence function; s5, a visual interface is provided, a user is allowed to check detailed information of the plants by clicking map marks, the detailed information comprises names, photos and statistical results, through the plant classification marking method, the types, the number and the distribution of the vegetation in the statistical area can be systematically analyzed, data are accurate, and presentation is visual.

A method for crowd-sourcing lane line map data for a vehicle includes receiving a plurality of observations. The method also includes classifying the plurality of observations into a plurality of observation categories. Each of the plurality of observation categories includes at least one of the plurality of observations. The method also includes determining a plurality of aligned point clouds based at least in part on the plurality of observations. One of the plurality of aligned point clouds corresponds to each of the plurality of observation categories. The method also includes determining a plurality of lane line maps based at least in part on the plurality of aligned point clouds. One of the plurality of lane line maps corresponds to each of the plurality of aligned point clouds. The method also includes updating a map database based at least in part on the plurality of lane line maps.

The invention relates to a three-dimensional digital contour detection system for a tunneling roadway, and belongs to the technical field of roadway contour measurement. The system comprises a data acquisition module used for acquiring original point cloud data through a three-dimensional scanning device; the data preprocessing module is used for preprocessing the original point cloud data to obtain actual point cloud data, constructing design point cloud data and aligning the actual point cloud data with the design point cloud data to obtain standard point cloud data; the over-break and under-break area division module is used for dividing over-break and under-break areas according to the design point cloud data; the plane screening module is used for fitting a plurality of random planes and screening out a plurality of initial candidate planes; the roadway size calculation module is used for classifying five actual planes and calculating the roadway size of the tunneling roadway based on the five actual planes; and the visualization and storage module is used for visually displaying the roadway contour information. According to the invention, the error of tunneling roadway contour measurement is reduced, and the efficiency and real-time performance of roadway contour construction are improved.