3507 results about "Cartography" patented technology

The invention relates to the technical field of image processing, in particular to a remote sensing monitoring method and system for cultivated land protection, and the method comprises the following steps: obtaining a remote sensing image sequence of a cultivated land region at a differential time node, extracting pixel gray values of the same land parcel, arranging the pixel gray values according to time, calculating the ratio of a difference value between adjacent frames to an intra-frame gray average value, and obtaining a remote sensing image sequence; and marking positions continuously exceeding the fluctuation reference ratio, and generating a pixel region set. According to the method, a sampling frequency threshold optimization strategy is adopted, abnormal areas are screened in combination with albedo change rate, short-time fluctuation interference is reduced, time sequence consistency is enhanced, a solar incident angle and a terrain slope are introduced to calculate projection influence, a slope surface shielding area is eliminated, and space grid marking and boundary integrity judgment are adopted; the method improves the continuity of cultivated land distribution information, combines time sequence analysis, sampling optimization, physical characteristic compensation and spatial consistency correction, enhances the fine recognition of the dynamic change of cultivated land, and improves the monitoring precision and data reliability.

According to the cultural relic mural three-dimensional digital protection and micro-change detection method, non-contact and damage-free image data acquisition and calculation are performed on the mural collection wall painting by using a digital photogrammetry correlation technology, and an orthographic image DOM and a digital surface model DSM of the mural collection wall painting are obtained. Color management is implemented in the links from data acquisition, calculation to result display, so that the color of the obtained digital orthographic image of the mural is consistent with the color of the actual mural. And carrying out fresco disease change analysis detection on the obtained fresco orthoimage and the digital surface model in a combined manner, obtaining the position and the area of the disease change, identifying the type of the disease, and finally outputting a fresco micro-change detection result extraction image. Scientific detection means and evaluation methods are provided for mural protection, and the efficiency of mural protection work is greatly improved. Meanwhile, detection data are analyzed, the change rule of the mural is mastered, the micro change trend of the mural is predicted, and the mural is effectively protected.

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 relates to the technical field of remote sensing landform enhancement, and discloses a remote sensing landform enhancement algorithm, which comprises the following steps of: S101, preprocessing an existing high-resolution DEM (Digital Elevation Model) image and an existing low-resolution DEM image to construct a training data set; step S102, constructing a double-domain multi-scale attention fusion super-resolution network; step S103, training the double-domain multi-scale attention fusion super-resolution network through the training data set; according to the method, the edge information and spatial continuity characteristics of the DEM image are comprehensively considered, the high-frequency and low-frequency information of the DEM image is extracted through Haar wavelet transform by utilizing the characteristic that a wavelet domain is highly sensitive to the high-frequency and low-frequency information, and spatial domain feature information obtained by a parallel branch convolutional layer is combined, so that the high-frequency and low-frequency information of the DEM image is obtained. Through fusion of the two, the network has a feature enhancement function in a shallow layer, and meanwhile, the importance relationship between different depth feature maps is obtained through the multi-scale attention fusion module group, so that the precision of DEM super-resolution reconstruction is improved.

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 the technical field of ocean exploration, in particular to a non-buried submarine pipeline identification method and system based on multi-beam point clouds, and the method comprises the steps: obtaining three-dimensional point cloud data of a submarine pipeline region, and carrying out the preprocessing of the obtained point cloud data; performing neighborhood construction based on the preprocessed point cloud data, setting a mask attention mechanism according to a neighborhood structure, performing geometric coding and feature enhancement by using an output result of the mask attention mechanism, performing decoding operation on the enhanced features, recovering feature representation of the complete point cloud, and performing suspended span height calculation and verification based on a segmentation result. According to the method, a decoding strategy combining reverse distance weighted interpolation and jump connection is adopted, enhanced features are accurately propagated to the original point cloud, the seabed datum plane is fitted through the reverse distance weighted interpolation, and the high-risk suspended cross area can be rapidly positioned.

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, which relates to the technical field of smart text travel, discloses a historical scenic spot-oriented generative smart text travel guide system comprising a historical scenic spot image acquisition module, a pre-training large model module, an image-text understanding module, a poem generation module and an output display module. The invention further discloses a historical scenic spot-oriented generation type smart text travel guide method. The method comprises the following steps of: acquiring an image; extracting feature information; constructing a large-model language knowledge structure, and understanding the cultural connotation of the historical scenic spot; comprehensive information about historical scenic spots is acquired; generating poems conforming to the cultural background and the poem rhythm of the historical scenic area; and displaying the generated poems to tourists through the AR technology. According to the invention, by integrating image acquisition and processing, a large language model, multi-modal data fusion and augmented reality technologies, immersive and personalized guide experience rich in historical culture connotation can be provided for tourists in historical scenic spots, and the visiting experience of the tourists is improved.

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 for enabling a communication device to determine a geographic location, corresponding to its own geographic location, by computing a polygon-shaped geographical region that surrounds the geographic location of the communication device are disclosed. To compute the polygon-shaped geographical region, a processor at the communication device selects a set of location information corresponding to received geographical coordinates of multiple location-enabled devices. The polygon-shaped geographical region is determined such that each of the plurality of location-enabled devices is located along a perimeter of the polygon-shaped geographical region and such that the communication device is located within the polygon-shaped geographical region.

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.

A high-definition (HD) map-related map construction method, electronic device, and storage medium are provided. The method includes: extracting a bird's-eye view (BEV) feature map based on the data; determining map information through a hybrid decoder based on the BEV feature map and a hybrid query; and constructing an HD map corresponding to the data based on the map information, wherein the map includes a plurality of map elements each including an area formed by a plurality of coordinate points in the map, the map information comprises coordinate information and class information of the plurality of map elements, and the hybrid query includes a plurality of hybrid features each corresponding to one map element and including a point feature and an element feature. Optionally, the method may be executed using an artificial intelligence (AI) model.

The invention discloses an AI-based staple map automatic generation method and system, and particularly relates to the staple map generation technology field, a radio frequency transmit-receive device and an unmanned aerial vehicle are used to collect boundary line inflection point coordinates of a staple and intersection point coordinates of the staple and an adjacent staple boundary line, and the inflection point coordinates are connected in sequence to obtain a staple boundary line; then, a land parcel boundary line and a land parcel area are corrected and judged, a land parcel area correction link is directly entered if a land parcel boundary line correction task is not triggered, a land parcel boundary point correction link is entered if a land parcel area correction task is not triggered, and a point which can better represent a land parcel trend is screened out from multiple inflection points to serve as a boundary point; according to the method, the problem that the boundary point processing workload is large is solved, meanwhile, the land parcel area is controlled to be consistent with the actual land parcel area, the land parcel boundary line is controlled to be consistent with the actual land parcel boundary line, the four boundaries of the land parcel are analyzed, and the accuracy of a subsequent land parcel map is guaranteed to a certain degree.

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.

The invention discloses a building roof elevation extraction method and system based on city modeling, and the method comprises the steps: S1, point cloud data and image data fusion registration: extracting data features, and carrying out alignment registration; s2, roof denoising and boundary optimization: identifying interference information, extracting a roof boundary, and generating a roof digital surface model through interpolation; s3, roof elevation extraction: for a flat roof, extracting the top elevation of the flat roof through a plane fitting method; for the slope top roof, extracting the top elevation of the slope top roof through an extreme point detection method; and extracting the top elevation of the roofs except the flat roofs and the slope roofs through a point cloud clustering method. According to the scheme, the roof elevation can be rapidly and accurately extracted, and high-precision three-dimensional data support is provided for urban planning, energy assessment and disaster emergency; the problems that in the prior art, roof elevation extraction efficiency is low, complex roof structure recognition precision is insufficient, and multi-source data fusion is difficult are solved.

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 provides a basement scene automatic vector map construction method and system, and the method comprises the steps: carrying out the IPM conversion of a plurality of ground-oriented top view images, carrying out the splicing, obtaining a bird's-eye view, carrying out the semantic segmentation of the bird's-eye view, extracting semantic elements, and converting the semantic elements into point cloud data; providing IMU and vehicle wheel speed data, combining with the point cloud data to construct a local map, and correcting to obtain a semantic point cloud map; preprocessing the semantic point cloud map, and clustering the point cloud data in the semantic point cloud map according to the similarity semantic point cloud to obtain clustered point cloud data; and based on the semantic point cloud map, combining the clustering point cloud data, constructing boundaries on two sides of a road, generating a lane center line and a boundary line, obtaining a vector map, embedding parking space information, and performing curve optimization on the center line and the boundary line, so as to obtain a basement scene automatic vector map. Vector representation of the complex environment of the underground garage is achieved, and high-quality basic map data support is provided for applications such as vehicle navigation and path planning.

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.

Various embodiments relate to a method, apparatus, and machine-readable storage medium including one or more of the following: receiving, from a user, a command to tag an object currently in view of a camera and located within a physical space; in response to the command, determining a distance from a location of the camera to a location of the object; determining the location of the object based on the determined distance; storing the location of the object and a label together as a tag in a digital twin representing the physical space; displaying a representation of the physical space; and displaying an indicator of the tag at a location in the representation of the physical space corresponding to the location of the object.

The invention discloses a typhoon nascent identification method based on a double-AI model architecture and typhoon asymmetry characteristics, a medium and a program product, and belongs to the technical field of meteorological monitoring and artificial intelligence, and the method comprises the steps: firstly, obtaining multi-channel satellite image data, and carrying out the preprocessing; then, the cloud cluster center is positioned through a first AI model; taking the center of the cloud cluster as a reference, and extracting symmetry features and asymmetry features of the cloud cluster; analyzing the extracted features through a second AI model, and judging whether the target cloud cluster is in a typhoon primary stage or not; and finally, outputting identification results including the typhoon center position, the birth time, the development probability and the like. According to the method, the accuracy and the reliability of typhoon nascent identification are effectively improved through staged identification of the double-AI model architecture in combination with the unique asymmetry characteristic of the cloud cluster, and the method has a relatively high practical value.

The invention discloses a Chinese style garden programmed generation method and system, and the method comprises the steps: firstly, carrying out the land and water terrain division according to the land and water distribution data drawn by a user, generating a terrain mask graph, and providing a basis for the subsequent layout; secondly, in a garden layout generation stage, the system screens an area suitable for building placement from the terrain mask graph, optimizes the building layout by using a WFC algorithm in combination with a 3D texture mapping technology, generates a preliminary layout white-box model conforming to garden rules, and optimizes building orientation and path connectivity; and finally, in a single building generation stage, the system generates a building model comprising a framework and a small component structure according to building parameters input by a user, and decoration details are added to perfect the appearance of the building. According to the method, the basic rules and diversified expression requirements of the Chinese style building are met, the learning cost of the user can be reduced through parameterized adjustment and interaction functions, the creation efficiency is improved, and the digital generation effect and the propagation effect of the Chinese style garden are remarkably improved.

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 belongs to the field of robot and computer vision, and particularly relates to a visual SLAM (Simultaneous Localization and Mapping) back-end optimization technology based on a data self-adaptive iterative reweighted robust kernel. Comprising the following steps: S1, a front-end data reading and processing module: a robot carries a camera to collect an image, performs feature extraction and feature matching on the image, and generates an initial camera pose and map points; s2, a rear-end optimization module: according to the initial camera pose and map point generated at the front end, calculating a median absolute deviation in an adaptive strategy, calculating a robustness parameter, then substituting the median absolute deviation and the robustness parameter into a target function, simplifying the target function by using an iterative reweighting strategy, and finally solving the optimal camera pose and map point by using an L-M algorithm; s3, the loopback detection module detects loopback according to whether the robot reaches a previous position or not, and transmits information to a rear end for processing; and S4, constructing a map module: constructing an environment map according to the optimized camera pose and map points.

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 present application provides a map generation method and apparatus. The map generation method is applied to a client, and comprises: in response to a map generation request, acquiring at least two map tile files; converting pixel coordinates included in the at least two map tile files, and on the basis of the conversion result, determining target map tile files respectively corresponding to at least two map tiles; creating a map generation task on the basis of the at least two target map tile files; and by executing the map generation task, rendering layers corresponding to the at least two map tiles sequentially in accordance with layer display priorities, and on the basis of the rendered layers corresponding to the at least two map tiles, sequentially displaying target maps associated with the layer display priorities.

The technology introduces 3D Moments, a new computational photography effect. As input a pair of near-duplicate photos is taken (FIG. 1A), i.e., photos of moving subjects from similar viewpoints, which may be very common in people's photo collections. As output, the system produces a video that smoothly interpolates the scene motion from the first photo to the second, while also producing camera motion with parallax that gives a heightened sense of 3D (FIG. 1B). To achieve this effect, the scene is represented as a pair of feature-based layered depth images augmented with scene flow (306). This representation enables motion interpolation along with independent control of the camera viewpoint. The system produces photorealistic space-time videos with motion parallax and scene dynamics (322), while plausibly recovering regions occluded in the original views. Experimentation demonstrating superior performance over baselines on public benchmarks and in-the-wild photos.