198 results about "Spatial extent" patented technology

The invention provides an unmanned aerial vehicle inspection defect sample generation method and system based on a diffusion model, and relates to the technical field of data processing, and the method comprises the steps: collecting an image of equipment, carrying out the feature compression and mapping operation of the image, carrying out texture gradient analysis and region density calculation, recognizing a local region with strong texture change in the image, and carrying out the feature compression and mapping operation; the method comprises the following steps: performing continuous aggregation on a local area, simulating a space range of defect growth, calculating a gradient difference value, determining consistent distribution of an image on a physical structure, determining a diffusion direction and a boundary position of a defect generation process, performing center feature extraction on the image, and determining a defect starting point and a growth speed of the defect generation process. And performing back diffusion to construct defect features, performing feature fusion on the defect features and the potential image data to obtain mixed image data, and performing feature reduction and image reconstruction to obtain defect image sample data. The defect sample can be reversely generated according to the equipment image.

The invention relates to the technical field of ocean engineering digital twinning and three-dimensional visualization, and provides a method and system for generating dredging terrain twinning based on a right-angle triangular mesh, and the method comprises the steps: obtaining regular grid elevation unified to an engineering plane coordinate system or preprocessed sampling height data, determining a covered space range, reading the space range and density parameters, and calculating the total row number and the total column number of the grids based on the space range and the density parameters; generating regularly arranged vertexes in the covered space, and constructing a topological structure of an isosceles right triangle grid; dividing the global grid into a plurality of Chunk blocks according to a fixed size by taking a vertex as a unit, establishing a triangular index mapping relationship between global rows and columns and the Chunk blocks, filling three vertexes of an isosceles right triangle and elevation / height data in each Chunk block in parallel, and generating local VBO, IBO and AABB; and performing batch rendering and coloring according to a height color table on all Chunk blocks to realize visualization of the terrain.

The invention discloses a real-time flight conflict detection method based on digital gridding. The method comprises the steps of dividing airspace grids, managing a three-dimensional space, dividing nodes according to a spatial range, and storing a specified number of grid units in each node; when the node capacity exceeds a threshold value, the node capacity is automatically subdivided into a plurality of sub-nodes, and recursive division of the space is realized; realizing grid query and insertion through spatial cross judgment; acquiring real-time flight path data of the aircraft, and mapping the real-time flight path data into the corresponding grid units according to the position of the real-time flight path data in the airspace; the track data comprises latitude and longitude, height and speed; and dividing conflict detection tasks of each grid unit and adjacent grids into a plurality of sub-tasks for parallel processing, generating a global conflict result set, and realizing large-scale real-time flight conflict detection. According to the invention, the flight conflict can be rapidly and accurately detected.

The invention discloses an HBase-based spatio-temporal index generation method and system, and the method specifically comprises the following steps: 1, collecting trajectory data, and carrying out the preprocessing of the trajectory data; step 2, generating administrative division codes and geographic grid codes based on the preprocessed trajectory data, and processing timestamps in the data trajectory; 3, splicing the administrative division codes, the geographic grid codes and the processed timestamps to form row key data of the HBase; and step 4, storing the row key data in the HBase to generate a row key index of the HBase, the row key index being used for spatial range, time query and nearest neighbor query.

The invention belongs to the technical field of geographic information technology and remote sensing image processing and service, and discloses a slice-free image service system and method based on dynamic projection and real-time mosaic, which abandons the traditional pre-slicing mode, directly provides online service based on original image data, and improves the service efficiency. The problem of redundant storage caused by pre-generation and storage of massive tiles is fundamentally eliminated, and storage space is saved by up to 90%. Meanwhile, when the original data is updated, the system does not need to carry out a time-consuming re-slicing process, real-time updating and publishing of services can be realized, and the core pain points of long data updating period and high delay in the traditional technology are thoroughly solved. Through the integrated dynamic projection engine and the real-time mosaic module, the on-demand service request of the client for any coordinate system, any spatial range and any resolution can be responded.

The invention discloses a grid-coding-based video space-time retrieval method and device, the grid-coding-based video space-time retrieval method is executed in computing equipment, and the method comprises the following steps: mapping a coordinate range of a target area into a corresponding grid code set according to a Beidou grid standard on the basis of the coordinate range of the target area; acquiring video data with an intersection or inclusion relationship between the spatial range of the shot object and the target area; combining the shooting time of any video data with each grid code to generate a space-time grid code set; constructing an index structure corresponding to the video data by taking each time-space grid code in the time-space grid code set as a main key; and in response to query information of the user, analyzing a space-time range in the query of the user, mapping the space-time range into a corresponding space-time grid code range, executing retrieval based on the range, and returning hit video data. According to the method, rapid positioning and accurate retrieval of large-scale aerial photography video data are realized.

The invention belongs to the technical field of spatial data processing, and particularly discloses a multi-source remote sensing data gridding construction and processing method and system, a terminal and a medium. Comprising the following steps: acquiring remote sensing image data, vector data, point cloud data and TIN data to form a standardized data set; performing three-dimensional layered mesh generation on the target area to generate an initial multi-level mesh set; performing geometric superposition and coverage judgment on the standardized data set to form an element-grid mapping set; performing double-engine coding and decoding on the grid units in the mapping set, generating a unique grid code, and establishing a code-space range mapping table; constructing a three-dimensional space topological structure; obtaining a space intersection result, a space union result and a space difference result; a multi-scale grid set is generated, and a unified gridding integrated data set is formed. Through gridding fusion and self-adaptive multi-scale processing of multi-source data, integrated expression and efficient organization of multi-source remote sensing data in a three-dimensional space are realized.

The invention provides a robot dog intelligent inspection control method and system for an open environment, and relates to the technical field of data processing.The method comprises the steps that the space range of inspection environment data is divided into a plurality of space units, each space unit is marked as a region paragraph, and each region paragraph is marked as an area paragraph; the method comprises the following steps of: obtaining a plurality of regional paragraphs, establishing cross-segment marks among the regional paragraphs to form a recursive chain, calculating the route change transmission degree of each regional paragraph in the recursive chain to obtain recursive feature intensity, layering each regional paragraph in recursive chain data, generating regional paragraph sets with different intensity levels, and obtaining a recursive feature set; and calculating the periodic aggregation degree of each area paragraph in each inspection period to obtain periodic paragraph intensity, correspondingly binding each area paragraph in the rearrangement sequence data with a preset action set to obtain action control data, and generating a control instruction according to the action control data. According to the method, superposition and amplification of tiny offset in control circulation can be avoided, and the problem of interruption of the inspection process caused by frequent correction is solved.

The invention belongs to the technical field of computer vision, and discloses a semantic edge guided three-dimensional scene reconstruction method based on an SDF diffusion model. The objective of the invention is to solve the problems of high bandwidth occupation of input data, poor structural consistency and insufficient reconstruction quality in traditional three-dimensional reconstruction. A point fine segmentation and gradient semantic edge extraction method is provided, edge information with consistent semantics and rich geometric details is extracted, and lightweight scene representation retaining key geometric information is realized. On the basis, a three-dimensional reconstruction framework of staged diffusion is proposed: firstly, a global occupancy field is generated to determine an object space range; then executing high-resolution SDF diffusion in the local area to recover a fine geometric surface; and finally, carrying out space alignment and fusion to ensure the consistency of a reconstruction result under a global coordinate system. According to the method, the geometric accuracy, semantic consistency and resource overhead of reconstruction are effectively balanced, and a novel solution is provided for high-quality three-dimensional scene reconstruction under a low-bandwidth condition.

The invention relates to the technical field of artificial intelligence, and provides an attention calculation optimization method, electronic equipment, a storage medium and a program product, and the method comprises the steps: generating a bounding box list of an attention matrix based on the mask information of attention calculation, the bounding box list comprises at least one effective bounding box, and the effective bounding box is used for generating an attention matrix; the effective bounding box is used for defining a spatial range of a target data block to be subjected to attention calculation in the attention matrix; and based on each effective bounding box in the bounding box list, loading a target data block corresponding to each effective bounding box from a query matrix, a key matrix and a value matrix, and executing attention calculation on the loaded target data block to obtain attention output corresponding to each effective bounding box. According to the method, the bounding box list is generated, and only the data blocks in the effective bounding boxes in the bounding box list are loaded and attention calculation is executed, so that invalid calculation and computing power resource waste are avoided, and the overall calculation performance is improved.

The invention discloses a structured corpus generation method and device for geological map multi-modal large model training, and the method comprises the steps: preprocessing geological vector data, and constructing a semantic aligned geological data set; randomly selecting a data viewport, and setting the geographic space range and size of a map viewport; configuring a plurality of visual parameter items, performing controllable random adjustment on text labels, element symbols and map maps, and customizing and producing geological map samples as required; extracting multi-dimensional attribute information of the geological map sample to construct structured meta-information annotation data, and constructing a geological element mask annotation file to obtain a structured corpus for geological map multi-modal large model training. According to the method, large-scale production of the training samples with diversity, high quality and image-text alignment features is realized, the geological map corpus meets the requirements of multi-modal large model training on data scale, diversity, labeling precision and modal alignment, and the training efficiency and generalization ability of a geological map intelligent interpretation understanding model are remarkably improved.

The invention provides a geographic JSON data generation method and device, equipment, a medium and a program product, and relates to the technical field of artificial intelligence. The method comprises the steps that geographic semantic keywords are obtained, and the geographic semantic keywords are used for representing the query intention of a user in a geographic space; converting the geographic semantic keywords to obtain a target space range; space objects in the target space range are screened, a candidate space data list related to the target space is obtained, and the candidate space data list comprises identifiers corresponding to one or more candidate space objects; extracting position information and attribute information corresponding to each candidate spatial object in the candidate spatial data list, and constructing a geographic information cue word; and inputting the geographic information cue word and a preset GeoJSON format template into a pre-constructed large language model, and outputting GeoJSON data. According to the method and the device, the GeoJSON data generation efficiency can be improved, and meanwhile, the labor cost involved in the process is reduced.

The invention relates to the technical field of three-dimensional vision and robot perception, in particular to a belt conveying line multi-camera point cloud real-time splicing method and system based on GPU acceleration. The point cloud real-time splicing method comprises the following steps of S1, collecting point cloud data of objects on a belt conveying line through a plurality of depth cameras; s2, performing spatial range filtering of the point clouds in parallel by using a GPU, and removing invalid points; s3, point cloud coordinate transformation is executed in parallel by using a GPU, and the point clouds of all the cameras are uniformly converted into the same world coordinate system; s4, performing triple filtering processing on the transformed point cloud to realize noise suppression, downsampling and density equalization; s5, fusing the filtered point clouds to form a complete scene point cloud; and S6, publishing the fused point cloud data through an ROS mechanism. GPU parallel computing is utilized, multi-camera point cloud high-speed real-time splicing is achieved, denoising equalization is effectively achieved through triple filtering, the processing efficiency and precision are remarkably improved, and the method is suitable for long-distance industrial monitoring.

The invention discloses a method and device for supporting multi-radar high-resolution networking and a storage medium, and relates to the technical field of radar data processing. The method comprises the following steps: determining a space range of a networking field; according to the spatial range and the target resolution, defining a grid structure of a networking field data body; allocating computing resources for high performance computing; aiming at each radar, pre-calculating a mapping area of the detection range of the radar in the grid structure; loading the original polar coordinate observation data of each radar into the computing resource in parallel; solving a networking value of each grid point in the grid structure layer by layer based on the mapping region and original polar coordinate observation data, and generating a networking result; and post-processing and storing the networking result, and releasing the computing resources. According to the method, the solution is directly solved from the original polar coordinate observation data based on the mapping region, so that the generation and conversion of massive intermediate data are avoided, and the technical bottleneck of huge memory and video memory consumption is fundamentally solved.

The application discloses a kind of forest scene voxel model construction method and system, the method includes: based on laser radar obtains the point cloud data of reference tree of the region to be measured and the point cloud data of canopy structure;According to the point cloud data of canopy structure, the point cloud data of reference tree is carried out point cloud conversion, and the point cloud conversion data of reference tree is obtained;According to the point cloud conversion data of reference tree, the blank of the point cloud data of canopy structure is filled with reference tree, and high-density point cloud data is generated;High-density point cloud data is voxelized, and forest scene voxel model is constructed.The system includes: data acquisition module, point cloud conversion module, data filling module and construction module.Through using the application, it can be realized in large space range to reconstruct the fine scale three-dimensional structure of forest scene and improve resolution.The application is a kind of forest scene voxel model construction method and system, and can be widely applied to laser radar data three-dimensional modeling technical field.

The invention discloses a multi-dimensional construction safety risk management and control method for a high-altitude highway, particularly relates to the field of construction risk management and control, and is used for solving the problems of slope monitoring lag and passive safety management and control caused by complex terrain in the existing high-altitude highway construction process. The method comprises the following steps: acquiring aerial survey images and laser point cloud data of a construction slope area according to a fixed period, generating a time sequence three-dimensional live-action model sequence, identifying and tracking natural feature points and artificial structure feature points in the model sequence, calculating a feature point displacement field based on precision registration among multiple periods of models, and obtaining a feature point displacement field. The method comprises the following steps: identifying risk deformation data in space-time association with a construction activity in combination with historical construction activity records, performing spatial clustering analysis on the risk deformation data to mark a potential instability region, and generating a prospective construction risk grading control signal according to the space range of the potential instability region and construction information data; and dynamic pre-judgment and graded response of high-altitude highway construction risks are realized.

The invention provides a multi-person posture estimation method and system based on topology perception dynamic association, and relates to the technical field of computer vision, and the method comprises the steps: synchronously obtaining a plurality of initial human body instance sets in an image and a corresponding initial key point set in each initial human body instance set based on a multi-scale feature map, generating a preliminary topological association between the human body instance and the key point; for each key point in the initial key point set, dynamically adjusting the spatial range of the key point based on the global context feature of the human body instance to which the key point belongs and the local semantic feature of the key point, and generating a dynamic key point frame; based on key point features extracted by the dynamic key point frame, key point relation reasoning is carried out based on a topology perception correlation model, key point positioning is optimized, grouping from key points to human body instances is completed, and a final multi-person posture estimation result is output. According to the method, the technical problems of poor robustness and insufficient precision of the existing multi-person attitude estimation method in a complex scene are solved.

A phase-difference-based high-resolution azimuth estimation algorithm for a small-aperture array with multiple targets comprises the following steps: 1) according to various array structures, the coordinate vectors of the array elements are subtracted and then combined accordingly to obtain new vectors along each coordinate axis; 2) the phase of each array element is obtained by performing a fast Fourier transform on the array element sampling data, the phase difference between the array elements is obtained by subtracting the phase of each array element, and the phase differences are combined according to the combination of the array element coordinate vector differences to extract the component k of the incident direction along each coordinate axis. x , k y and k z 3) After obtaining the various components of the incident direction, the unambiguous incident angle across the entire spatial range is calculated using inverse trigonometric functions. This invention utilizes a combination of array element sampling data to achieve more accurate target direction estimation, enhances resistance to noise and other interference, and broadens the applicable frequency band, enabling flexible application to various arrays, as well as direction estimation using multi-line spectrum signals and broadband signals.

This invention discloses a project status management method and system for intelligent point cloud modeling, relating to the field of project status management technology. The method includes registering point cloud block files, label files, and 3D model files generated during point cloud segmentation, point cloud partitioning, geometric fitting, and pipeline parameter adjustment as subsequent versions and recording operation impact information; constructing a 3D spatial index structure to associate and store point cloud block files, pipeline objects, and corresponding operation impact information; and when a rollback request is received, determining the set of objects that intersect with the target 3D spatial range and whose semantic category belongs to the target semantic category set, and determining the set of affected objects whose version number is later than the target version identifier. This invention can, upon receiving a rollback request containing the target spatial range and the target semantic category set, only locate the affected local object set and perform a local rollback, which helps to preserve the modeling results of unaffected areas and reduces redundant processing and manual verification work.

The invention discloses an urban space type identification method based on a mixed density clustering algorithm, and relates to the technical fields of smart cities, urban planning, tourism planning, urban traffic and the like, and the method comprises the steps: constructing a data set for urban space type identification for a research area; based on the constructed data set, urban space division processing is carried out by using a DBSCAN density clustering algorithm, and an obtained result is marked as a clustering result D; performing unique clustering processing on each category S in the D based on a C-means clustering or Gaussian mixture model (GMM) algorithm to obtain a central point position P of each category S; counting the number of facility POIs in a local spatial range for the central point position P of each category S, and recording an obtained result as a local spatial information counting result; and determining the type of each category in the clustering result D according to a local spatial information statistical result. According to the invention, clustering of the service point space data set and identification of the urban space type can be realized based on the design of the mixed density clustering algorithm.

The invention discloses a neutral atmosphere refractive index calculation method and system suitable for different heights, and belongs to the technical field of communication and navigation. During modeling, monthly average reanalysis data is used as input to calculate the three-dimensional refractive index field of the neutral atmosphere, and horizontal, vertical and time domain change characteristics of the refractive index are represented by adopting a regular grid, a third-order index and a trigonometric function; when in use, the refractive index of any target point at any time within a global near-surface space range of 85 km can be calculated through space-time interpolation and elevation normalization only by giving the longitude, latitude, geodetic height and simplified Julian day of the target point. According to the method, the empirical modeling of the global neutral atmosphere refractive index field is realized by utilizing reanalysis data for the first time, the refractive index calculation precision at different height positions is improved through third-order index elevation normalization, and the method has important application value in the communication and navigation fields such as electromagnetic wave signal propagation path simulation and neutral atmosphere delay calculation correction.

Methods and systems for performing K-nearest neighbour (K-NN) queries on a spatial dataset in a distributed or parallel computing system are described herein, where the spatial data comprises query data and object data. The spatial dataset is pre-processed, whereby the query space (i.e., the spatial extent of the query data) is partitioned according to a particular partition scheme. For each partition, an area (defined as the object range of the partition) is calculated based on the geometry of the partition and a set of K candidate objects allocated to that partition, with all objects within the object range defining the extent of any subsequent K-NN queries performed on that partition. When the query dataset is subsequently partitioned using the same partition scheme to perform a K-NN query, the pre-processed object range information can be used to retrieve the objects to be queried for each partition.

A method for determining target object extent data (40), which characterizes at least one spatial extent of at least one target object detected in at least one radar measurement with at least one radar system, a method for determining at least one point cloud (34), a method for determining a model (52) by machine learning, a radar system, and a model (52) are described. In the method for determining target object extent data (40), at least one model (52) determined by machine learning is executed. At least a portion of the raw radar data (50) acquired in at least one radar measurement is fed to at least one model (52) determined by machine learning, and corresponding target object extent data (40) are determined by the at least one model (52) based on the fed radar raw data (50).

The application discloses a map parallel superposition analysis attribute matching method and system based on Hilbert space coding, relates to the technical field of geographic information systems, determines a target region, reads and loads vector polygon data of a source layer and a target layer which need to be subjected to superposition analysis, calculates a geometric center point of each polygon, generates a globally unique Hilbert space code according to a space range, and analyzes the vector polygon data of the source layer. The application generates the globally unique Hilbert space code by calculating the geometric center point of the polygon, avoids the high complexity problem of geometric intersection operation in the traditional method, the uniqueness of the code ensures the accuracy of attribute matching, especially in the massive data scene, the parallel processing of the Hilbert space code significantly reduces the calculation time, meanwhile, the space filling characteristic of the code ensures that the codes of adjacent polygons are similar, further optimizes the locality of attribute transmission, and reduces invalid calculation.

The invention provides a high-temperature and drought composite disaster monitoring and early warning method and system, and relates to the technical field of disaster monitoring and early warning, and the method comprises the steps: 2, extracting a data subset from a fusion data set, constructing a feature analysis region according to a preset reference relation, selecting a core analysis unit in the feature analysis region as a focus of an ellipse, and carrying out the calculation of the data subset; selecting an external reference unit as another focus of the ellipse in an adjacent spatial range, and calculating the spatial form and dynamic change of an eccentricity quantization region of the ellipse; according to the incidence relation of the core analysis unit and the external reference unit along with the time change, an analysis path is generated, an environment parameter correction coefficient is calculated to calibrate related elements in the fusion data set, and a calibrated fusion data set is obtained. According to the invention, probability prediction and dynamic early warning of high-temperature drought composite disasters are realized, and the reliability and real-time performance of disaster early warning are improved.

This invention provides a method for security responsibility assessment and closed-loop traceability in smart governance scenarios, comprising: acquiring multi-source heterogeneous data in the smart governance scenario; generating a corresponding event identifier when an abnormal event is detected in the multi-source heterogeneous data; extracting a structured evidence package within a target time window and target spatial range based on the event identifier; extracting responsibility factors from the structured evidence package; inputting the responsibility factors into a responsibility assessment model and a responsibility scoring function to obtain the responsibility score, responsibility level, and responsibility confidence level corresponding to the abnormal event, and determining at least one of the direct responsible entity, related responsible entity, and management responsible entity based on the responsibility correlation; and automatically generating corresponding handling instructions based on the responsibility level and the category of responsible entity.

This invention relates to the field of artificial intelligence technology, providing an attention computation optimization method, electronic device, storage medium, and program product. The method includes: generating a bounding box list of an attention matrix based on mask information for attention computation, wherein the bounding box list includes at least one valid bounding box, which defines the spatial range of a target data block in the attention matrix to be subject to attention computation; loading the target data block corresponding to each valid bounding box from a query matrix, a key matrix, and a value matrix based on each valid bounding box in the bounding box list, and performing attention computation on the loaded target data block to obtain the attention output corresponding to each valid bounding box. This invention, by generating a bounding box list and loading and performing attention computation only on data blocks within valid bounding boxes in the list, avoids invalid computation and waste of computing resources, thereby improving overall computational performance.

The invention provides a method for establishing a spatial LCA data set, and relates to the technical field of life cycle evaluation and environment management, and the method comprises the steps: determining a data set target and a corresponding product / service, and defining a system boundary, a region boundary, a time boundary and a data quality requirement; then collecting basic unit process data including input / output streams and geographic positions; making a space division rule (including a space range, a grid shape and granularity) according to a region boundary and an application scene, and generating a grid system; attributing the basic unit data to the corresponding grids through space matching; aggregating the data in the grids according to a weighted average algorithm and other synthesis rules to generate synthesis unit process data; associating the grid geographic position identification to form grid unit process data; and finally, storing the original data and processing records in standard formats such as ILCD / EcoSpold2 and the like. The time-space consistency, traceability and multi-scene adaptability of data are ensured through a systematic process, and the method is suitable for the fields of environmental evaluation, carbon accounting and the like.

The invention provides a construction method and device of a space grid system and a program product, and the method comprises the steps: generating a first-level grid of the space grid system according to the position of each port and a preset route by taking each port and each route as a first-level metadata object; taking a first selected object contained in the port as a second-level metadata object, and generating a second-level grid of the space grid system; for each port, taking the second selected object as a third-level metadata object, and generating a third-level static grid of the space grid system; after a service use demand is received, dividing a third-level static grid associated with the service demand by using a bay length, and dynamically generating a third-level dynamic grid; attributes of the dynamic metadata object include a spatial range identified using bay bits as units. The technical scheme is more suitable for port logistics business logic, semi-semantic coding can be directly used for topology calculation, resources are saved, and real-time performance is improved.

The present application relates to the technical field of marine engineering digital twin and three-dimensional visualization technology field, provide a kind of based on right triangle grid's dredging topography twin's generation method and system, comprising: obtaining regular grid elevation or sampling height data after pre-processing that have been unified to engineering plane coordinate system, determine the space range covered read space range and density parameter, based on space range and total row number and total column number of calculated grid;In the space covered, generate regularly arranged vertex, construct the topological structure of isosceles right triangle grid;With vertex as unit, several Chunk blocks are divided into global grid with fixed size, establish the triangular index mapping relationship of global row and Chunk block, the three vertices of isosceles right triangle and elevation or height data are filled in each Chunk block in parallel, generate local VBO, IBO and AABB;Batch rendering and coloring according to height color table are executed to all Chunk blocks, and the visualization of topography is realized.