376 results about "Delaunay triangulation" patented technology

The present invention relates generally to effectively design a wiring of a semiconductor package, etc., in a short time. A wiring design software (SW) reads in design information indicating disposition of pads on a chip, disposition of pins on a package, and relationship of correspondence between the pads and the pins, analyzes it to prepare a wiring problem, classifies the pads and the pins into source and sink elements, and assigns consecutive identification numbers to the pads and the pins with a same identification number being assigned to a pad and a pin which are connected each other (S102, . . . , S108). The wiring design SW generates a virtual triangle having a source / sink element as an apex by applying Delaunay triangulation to the source and the sink elements (S110). The wiring design SW level classifies the pins using the generated triangle (S200). The wiring design SW determines whether or not an edge of the triangle crosses a wiring and connects the edges which are determined to cross each other to derive a route of wiring (S220), outputting the result of wiring design (S118).

Methods, apparatus and computer program products provide efficient techniques for reconstructing surfaces from data point sets. These techniques include reconstructing surfaces from sets of scanned data points that have preferably undergone preprocessing operations to improve their quality by, for example, reducing noise and removing outliers. These techniques include reconstructing a dense and locally two-dimensionally distributed 3D point set (e.g., point cloud) by merging stars in two-dimensional weighted Delaunay triangulations within estimated tangent planes. The techniques include determining a plurality of stars from a plurality of points pi in a 3D point set S that at least partially describes the 3D surface, by projecting the plurality of points pi onto planes Ti that are each estimated to be tangent about a respective one of the plurality of points pi. The plurality of stars are then merged into a digital model of the 3D surface.

The invention relates to a scattered point cloud Delaunay triangulation curved surface reconstruction method based on a mapping method and belongs to the field of a computer graphics and virtual reality technology. The method specifically includes the first step of obtaining original point cloud data of a target, the second step of obtaining K-level neighborhoods and unit normal vectors of all points in the original point cloud data, the third step of fragmenting the point cloud data, the fourth step of parameterizing fragmented point clouds to a two-dimensional plane, the fifth step of conducting Delaunay triangulation on the point clouds in the two-dimensional plane and mapping the point clouds back to corresponding three-dimensional space, and the sixth step of optimizing an initial triangle mesh model. Compared with the prior art, the scattered point cloud Delaunay triangulation curved surface reconstruction method based on the mapping method has the advantages that the quality of a triangle mesh can be ensured and triangle meshing on the scattered point clouds can be quickly realized when mesh modeling is carried out on large-scale point cloud data, and the method has a better effect on large-scale point clouds.

The invention provides a sampling point topological neighbor-based method for reconstructing a surface topology of a scattered point cloud. The method is characterized in that: topological neighbor reference data of a target sampling point is acquired by eccentrically extending and adaptively extending the target sampling point and k neighbors thereof; topological neighbors of the target sampling point are queried from the topological neighbor reference data, and matching points meeting the Delaunay condition are acquired from the topological neighbors in the same layer of the target sampling point to generate local Delaunay triangulation; and the surface topological reconstruction of the whole scattered point cloud is realized through increment extension. Instances prove that the method can reasonably reconstruct the surface topology of the scattered point cloud of seamless, border and other models, and effectively solves the problem that non-uniform point cloud easily has non-technological pores.

The invention belongs to the image processing technique and particularly relates to a rapid and self-adaptive generation algorithm of intermediate viewpoint based on left and right viewpoint images. In order to accurately obtain the multi-viewpoint three-dimensional images of twin lens, the image at the real virtual viewpoint is obtained. The technical scheme comprises the following steps of: inputting left and right viewpoint images picked up by a camera to extract angular points of left and right images; extracting the angular point pair matched with the left and right views by using a method of normalization covariation; performing Delaunay triangulation on the left and right views according to the extracted accurate matching point by a point-to-point inserting method; acquiring an inverse transformation matrix to each triangle grid of the virtual viewpoint image; acquiring a point of each point in the triangle grid corresponding to the left and right viewpoint images, endowing the pixel value of the corresponding point to the point in the intermediate virtual viewpoint grid, and finally generating an image of the intermediate virtual viewpoint. The invention is mainly applied to image processing.

The utility model relates to a dynamic modeling and control technique of a self-moving sensor network and belongs to the sensor network technology. According to the technical proposal provided by the utility model, the dynamic modeling and controlling technology of a self-moving sensor network comprises the steps: the step I: build a distributed moving sensor network model based on the local Delaunay triangulation and other applicable diagram; the step II: use two methods to perform the distributed self-arrangement and the self-organization in the network for the sensor controlling node of each region in the distributed moving sensor network model; the step III: use the formation algorithm to control the network node formation and the node cooperation to achieve the purpose of fully energy-saving; the step IV: build the ad-hoc route data transmission protocol of the self-organization network of the distributed mobile robots to realize the stable work of the entire self-moving sensor network. The utility model can provide an algorithm for the repeatable configuration, cooperation, route development and verification of the sensor network with a plurality of moving sensor nodes.

A wirelessly interactive dog collar is disclosed, comprising a neck collar having imbedded features that allow voice commands and tracking over long distances, along with features that facilitate tracking and visualization. The device comprises an elongated collar adapted to fit around a dog's neck having an internal compartment housing a cellular connectivity electronics module, a power supply and wiring to a plurality of speakers, light sources and a global positioning tracking antenna. The device provides a cellular phone antenna and means to transmit and receive voice transmissions through a cellular network, facilitating an owner's ability to track the animal and initiate voice communication. Light sources around the collar improve visualization of the pet at night, while the GPS tracking unit provides a backup to cellular triangulation, allowing location determination over long distances.

The invention relates to the technical field of computer graphics and image processing, in particular to a 3D human face modeling method based on front silhouette, which mainly models the 3D human face in a fully automatic manner. The method comprises the following steps: a general human face grid model is built by 113 feature points and 184 tri patch information arrays which are connected with the 113 feature points based on Candide parameterization; 2D position information and depth information of a specific human face are determined by virtue of human eyes location algorithm and side nose tip location algorithm by inputting two 2D images, the general face model is modified and transformed into a specific human face model; an interpolating is calculated for the human body patches by Delaunay Triangulation Technology and texture mapping is carried out by the Bilinear Interpolation Technology, thus causing the human face image to be appeared more delicate and accurate; and the method solves the problems such as low efficiency, high calculation expense, and the like, existing in the prior art.

The invention relates to the technical field of synthetic aperture radar interferometry, and specifically relates to a PSInSAR estimation method applicable to complex urban area infrastructure in windy and rainy conditions. The method includes following steps: performing data preprocessing on InSAR data; establishing a Delaunay triangulation network and an adaptive encryption network; estimating an arc segment relative parameter through a robust estimator; performing Tikhonov regularization adjustment operation; establishing a local star network; recognizing single PS points and layover PS points; calculating the single PS points in remaining pixels through the robust estimator, and detecting the layover PS points through a compressed sensing algorithm; and outputting heights and deformation results of the single PS points and the layover PS points. According to the method, combined calculation of the single PS points and the layover PS points is realized through mixed network establishment without removing the atmosphere in a global manner, a temperature non-linear deformation model is introduced, the fitting degree of the time sequence phase is improved, accurate estimation of the PS points is realized by employing the robust estimator, and the layover PS points of the complex urban environment are extracted by employing super-resolution MD-TomoSAR imaging.

The invention discloses an adaptive spatial clustering method, comprising the following steps of: (1) preprocessing spatial data and selecting features; (2) creating a Delaunay triangulation network according to spatial attribute; (3) performing clustering analysis operations according to the spatial attribute; (4) turning to a step (5) if a spatial solid obstacle is needed to be further considered, and turning to a step (6) if a thematic attribute is needed to be considered, otherwise, ending the spatial clustering operations; (5) introducing a spatial obstacle layer, performing overlap analysis on the spatial obstacle and the side length of the Delaunay triangulation network between the entities in each spatial cluster, and breaking the side length if the spatial obstacle is intersected with the side length; (6) performing the thematic attribute clustering by an improved density-based spatial clustering method; (7) visualizing the clustering result, and outputting the clustering result. The adaptive spatial clustering method is simple and convenient to operate, high in degree of automation, high in calculation efficiency, perfect in functions, strong in applicability and the like, and can effectively improve capability of spatial clustering analysis to excavate deep-seated geoscience rules.

A method for generating constrained Voronoi grids in a plane with internal features and boundaries is disclosed. The disclosed method generally includes approximation of internal features and boundaries with polylines based on plane geometry. Protected polygons or points are generated around the polylines, and Delaunay triangulation of protected points or protected polygon vertices is constructed. Delaunay triangulation that honors protected polygons or points is generated in the rest of the gridding domain. The constrained Voronoi grid is then generated from the Delaunay triangulation, which resolves all of the approximated features and boundaries with the edges of Voronoi cells. Constrained Voronoi grids may be generated with adaptive cell sizes based on specified density criterion.

The invention relates to a real-time three-dimensional visualization method of a large-scale scene city building based on spatial cognition. The method is based on a gestalt psychology and a city image theory. A single chain clustering method is used to cluster large-scale building models. Delaunay triangulation and broken line simplification methods are used to rapidly combine and simplify a classification result so as to establish a multiple-level of detail model of the city building and realize interactive three-dimensional visualization of the large-cene and high-density city building. The method provided in the invention accords with principles of approach, similarity, syntropy and the like in the gestalt theory and simultaneously essential factors, such as a city road, a boundary, a landmark city image and the like, can be maintained.

The invention discloses a high-resolution remote sensing image plane extraction method based on skeleton characteristics, comprising the following steps: selecting a remote sensing image edge detection algorithm based on embedded confidence coefficient for edge detection, and realizing the remote sensing image edge detection algorithm based on embedded confidence coefficient; vectorizing a groundfeature target edge; extracting a ground feature skeleton base line from the vector edge of a ground feature based on a constraint Delaunay triangulation network algorithm; carrying out the target main skeleton extraction algorithm based on a binary tree structure; carrying out feature analysis on the target main skeleton of the plane; and realizing the automatic identification method of a plane target. By means of the invention, the plane target can be automatically identified and extracted and better identification extraction effect is obtained. The plane target skeleton has the excellent characteristics of rotation invariance and high discrimination index with other ground features, the vector edge of the ground feature target can be efficiently and precisely extracted from a remote sensing image with high spatial resolution, and the improved target skeleton can be extracted.

The invention discloses a delaunay-triangulation-network-based multi-redundancy network RTK atmospheric error interpolation method. A network RTK data processing center constructs a Delaunay triangulation network based on a correct coordinate of a CORS base station; after a user is accessed to a data processing center, an optimal triangular unit and a suboptimum triangular unit of the location of the user are selected; an atmospheric error interpolation base line number is extended; an MLIM ionized layer interpolation model and an RELIM tropospheric interpolation model are established; and an atmospheric interpolation completeness monitoring method of a moving station in a grid is provided. The interpolation precision of the MLIM ionized layer interpolation model is higher than that of the traditional model by three times and the interpolation precision of the RELIM tropospheric interpolation model is higher than that of the traditional model by 6 to 30 times; and the two models can still have high interpolation precision at an area with a large elevation difference at the base station. A regional CORS ionized layer and tropospheric completeness index can reach a centimetre-level interpolation precision, so that real-time positioning completeness monitoring of a network RTK user can be realized. With the method provided by the invention, a CORS base station around a user can be utilized fully; the atmospheric delay interpolation precision of the area can be improved; and the rapid and high-precision positioning of the user can be guaranteed.

The invention discloses a detection method for a cargo volume and a bulk density of a train compartment, comprising the following steps of: obtaining two sets of distance detection data on an x-axis and a z-axis of the train compartment by using a two-dimensional scanner; performing a united computation on motion data of the car along the y-axis direction calculated by an OPC-Client system and thetwo sets of distance detection data to obtain the two sets of three-dimensional point cloud data; performing a down sampling and an irrelevant point removal processing on the obtained three-dimensional point cloud data to obtain two sets of streamlined three-dimensional point cloud data of the train compartment; creating a Delaunay triangulation network for two sets of streamlined three-dimensional point cloud data to obtain the top surface and the bottom surface of the train compartment; transforming a total volume of cargo in the train compartment into an aggregate form by a projection processing; calculating the volume of the transformed aggregate, performing a summation processing to obtain a total volume of the cargo in the train compartment; calculating a bulk density parameter of the cargo carried and judging the stability by using the calculated total volume of the cargo and the weight data provided by a rail weighbridge.

Unstructured grids are automatically constructed in a domain containing complex internal boundaries. Simulation grids are constructed for reservoirs or fields which contain complex fault planes. Reconciling among generated fault grid-points and other reservoir / field grid-points is performed, enabling the use of unconstrained Delaunay triangulation. High-quality orthogonal unstructured grids are provided with good convergence properties for reservoir simulation.

Orthogonal unstructured grids are automatically constructed for a field or reservoir model with two types of internal boundaries: complex wells and faults, or other discontinuities. The methodology is used to constructed simulation grids for reservoirs or fields which contains both complex fault planes and multi-lateral wells. A hierarchical grid point generation, prioritization, conflict point removal system is provided enabling the use of unconstrained Delaunay triangulation. High-quality orthogonal unstructured grids are produced with good convergence properties for reservoir simulation.

The invention discloses a triangular mesh hole-filling method based on a Hermite radial basis function. The method includes the following steps: after a hole boundary is extracted, on the basis of vertexes around a hole and normal information, utilizing the Hermite radial basis function to interpolate to acquire an implicit hook face; projecting the boundary to a plane, subjecting the hole boundary to limited Delaunay triangulation, and performing subdivision processing on a mesh after being triangulated; adjusting a newly-added triangle onto the implicit hook face to complete repairing. The triangular mesh hole-filling method is high in robustness and needless of manual participation and has good repairing effect on mesh holes large in curvature change.

The invention discloses a Delaunay triangulation network subdividing method based on space curved surface constraint. The method comprises the following steps of: rebuilding a space fractured layer curved surface by fractured layer data; initially rebuilding layer positions to acquire a space triangular curved surface; finding out a space triangle which crosses over the fracture surface in the area in which a reverse fracture layer exits and deleting the space triangle; filling a hole or a gap formed by deleting the triangle to ensure that a boundary of the space triangulation network is a convex shell or the edge generated by filling the edge of the area concave at random cannot cross over the fracture surface. The method has the active effects that a triangular part of the three-dimensional curved surface under the space curved surface constraint is proposed, so that the ground layer rebuilding problem under a complicated geologic structure condition is solved, and a technical support is provided for interpolation of layer positions, drawing of contour lines and the like.

The invention provides an automatic SAR (synthetic-aperture radar) image rectification method. In the method, the problems encountered when feature points are selected by SIFT (scale-invariant feature transform) rectifying points under the condition of SAR image complex landforms are analyzed, the feature points are combined with the Delaunay triangulation network and coded, and triangle similarity of coded feature points are judged through automatic threshold values according to the Delaunay triangularization principle. Since SIFT rectification and the Delaunay triangulation network have robustness to geometric changes such as rotation, wrong rectifying points rectified by the SIFT can be filtered by the SIFT-Delaunay encryption algorithm according to the similarity among triangles, and accurate rectification can be achieved.

A method for generating constrained Voronoi grids in a plane with internal features and boundaries is disclosed. The disclosed method generally includes approximation of internal features and boundaries with polylines based on plane geometry. Protected polygons or points are generated around the polylines, and Delaunay triangulation of protected points or protected polygon vertices is constructed. Delaunay triangulation that honors protected polygons or points is generated in the rest of the gridding domain. The constrained Voronoi grid is then generated from the Delaunay triangulation, which resolves all of the approximated features and boundaries with the edges of Voronoi cells. Constrained Voronoi grids may be generated with adaptive cell sizes based on specified density criterion.

The invention discloses an image splicing method based on grid deformation, relating to the technical field of image splicing. The method includes the following steps of S1 respectively extracting SIFT characteristics of two space adjacent images, and matching the characteristics; S2 performing iterative computation by means of an RANSAC algorithm and screening characteristic point pairs; S3 estimating the global projective matrix and performing global projective transformation; S4 by means of Delaunay triangulation, constructing a dense triangular grid for an overlapping region and constructing a sparse grid for a non-overlapping region; S5 establishing the grid deformation energy function and optimizing the global projective registration; and S6 fusing the images to produce a wide-view-field image. The dense triangular grid represents the overlapping region and the sparse triangular grid represents the non-overlapping region of the image, so that compared with the APAP method, the whole image uses dense and same matrix grids, the algorithm efficiency is greatly improved. Meanwhile, the grid deformation can make full use of the parallel and high-speed operation performance of the CPU, and the splicing speed can be greatly improved.

A method for rapid hierarchical image segmentation based on perceptually driven contour completion and scene statistics is disclosed. The method begins with an initial fine-scale segmentation of an image, such as obtained by perceptual completion of partial contours into polygonal regions using region-contour correspondences established by Delaunay triangulation of edge pixels as implemented in VISTA. The resulting polygons are analyzed with respect to their size and color / intensity distributions and the structural properties of their boundaries. Statistical estimates of granularity of size, similarity of color, texture, and saliency of intervening boundaries are computed and formulated into logical (Boolean) predicates. The combined satisfiability of these Boolean predicates by a pair of adjacent polygons at a given segmentation level qualifies them for merging into a larger polygon representing a coarser, larger-scale feature of the pixel image and collectively obtains the next level of polygonal segments in a hierarchy of fine-to-coarse segmentations. The iterative application of this process precipitates textured regions as polygons with highly convolved boundaries and helps distinguish them from objects which typically have more regular boundaries. The method yields a multiscale decomposition of an image into constituent features that enjoy a hierarchical relationship with features at finer and coarser scales. This provides a traversable graph structure from which feature content and context in terms of other features can be derived, aiding in automated image understanding tasks. The method disclosed is highly efficient and can be used to decompose and analyze large images.

The invention discloses a road network reconstruction method and system based on mobile phone positioning data. The method includes: acquiring an original dataset which includes a training dataset anda prediction data set, wherein the original dataset is formed by track points acquired according to mobile phone positioning data; respectively utilizing two dimensionalities like time and density toperform feature construction and combination on the training dataset and the prediction dataset, and generating a training set and a prediction set accordingly; using the generated training set, andacquiring a sampling point classifying model on the basis of an algorithm in machine learning; applying the learned classifying model to the prediction set to divide the track points into road pointsand non-road points; performing road reconstruction on the recognized road points on the basis of a constraint Delaunay triangulation network; according to a topological relation, modifying a road central line to complete reconstruction of a road network. A new mode for high-quality refined road network production and updating is put forward, so that technical support can be provided for seamlessnavigation technology, refined road networks especially, and coverage of path navigation service is expanded.

The invention discloses a Delaunay triangular net-based road center line extraction method, and belongs to the technical field of geographic information data processing. The method comprises the steps of establishing buffer regions of road line data, and performing buffer region fusion; performing node encryption based on a graphic layer of the established buffer regions, and establishing a Delaunay triangular net by utilizing encrypted nodes; classifying triangular elements forming the triangular net according to geometric features, thereby obtaining feature points of all the triangular elements; connecting the feature points in sequence to obtain single-line data, and obtaining a final result through curve smoothing. Single-line road network data is obtained by single and double-line mixed road data, so that complex manual processing or a data re-collection process is avoided when data is obtained in the field of scientific research such as road network analysis and the like or application, a topological relation of the road data can be well kept, and result data meeting the requirements is obtained.

The invention relates to a mass airborne LiDAR point cloud Delaunay triangulation network parallel construction method. The method comprises the following steps: carrying out data block division and task distribution on mass airborne LiDAR point cloud data; applying a pointwise insertion algorithm to each data block respectively so as to construct a sub-triangulation network in parallel, and acquiring a sub-triangulation network set; using a merging algorithm to connect the adjacent two sub-triangulation networks so as to generate the merged triangulation network; using an optimization algorithm to carry out optimization on a newly generated triangle and the adjacent triangle so as to obtain the merged triangle which accords with a Delaunay rule; repeating the merging and the optimization until all the sub-triangulation networks are merged and the complete Delaunay triangulation network can be obtained. The invention also provides a corresponding apparatus for executing the above method. By using the method and the apparatus of the invention, a post-treatment speed of the mass airborne LiDAR point cloud can be substantially increased. The method and the apparatus of the invention have great significance for practical application.

A novel, easy to use, and computational efficient rubber sheeting algorithm is designed for interactive image registration in a web-based application environment. The algorithm has two steps, including a piece-wise linear interpolation step to interactively find a suitable set of control points and displacement vectors, and a following optional global radial basis wrap step to generate smoother result using the final control point set. A dynamic Delaunay triangulation method is designed to efficiently update the decomposition of the image. Natural and intuitive wrapping result will be dynamically generated in real-time while the user interactively insert, delete or drag a control point. The number of control points is not limited, and a large number of control points can be used if necessary without compromising the performance of the algorithm. With enough control points specified using the piece-wise rubber-sheeting step, the wrapping result can be further smoothed by using the optional, click-button poly-quadric global wrapping method in the second step. The algorithm is implemented as a Java Applet and able to run as a cross-platform web-based application.

The invention discloses a crown appearance extract method based on shape analysis. The data treatment of the invention is characterized in that a laser scanner carries out single-sweep on a whole plant to obtain the single-sweep point cloud data of the plant; firstly, a root node is found from the point cloud data, and then the point cloud data is divided into branch point cloud and leaf point cloud by a shortest distance method; a corresponding skeleton is extracted from the branch point cloud, and the skeleton is divided into a plurality of parts according to the branching characteristics of a tree, and classified branch skeletons are utilized to classify the leaf point cloud; Delaunay triangulation is carried out on each classified leaf point cloud to obtain a tetrahedron and a triangular patch; the triangular patch is divided into three classes, such as exterior, interior, boundary and the like, wherein the triangular patch located on the boundary forms a sealed body which is used for representing the shape of the classified leaf point cloud; and the shape integration of each class of the leaf point cloud represents the shape of the whole crown.

The invention discloses a star-network-based BDS / GPS broadcast type network RTK algorithm. All base stations form a triangulation network based on a Delaunay triangulation algorithm; and a controllable full-region star network formed by a plurality of star network elements is generated based on the triangulation network. Data of the base stations are obtained in real time and network element calculation is carried out to generate a baseline atmospheric error. Meanwhile, a server side broadcasts a main station observation value, a base station coordinate and the baseline atmospheric error to auser by using the star network as a unit based on a UDP protocol; the user selects one network element based on an own approximate position and the position of the main station; interpolation is carried out on an inter-station single-difference atmospheric error of the baseline formed by the user and the main station and the obtained atmospheric error is corrected to the observation value of the main station to carry out baseline calculation. Besides, the user also can uploads an approximate coordinate by two-way communication and the server side broadcasts difference data of the network element in which the user is located. And difference data broadcasting by equipment like ground equipment, an aircraft or a satellite is also supported.