25 results about "Centroid" patented technology

Disclosed in the present invention is a matrix transformation-based improved design method for a diffuser. Firstly, inlet and outlet position information of a diffuser is extracted, and then a double-coefficient adjustable polynomial is used to design a central line of the diffuser between the centroid of an inlet section and the centroid of an outlet section, and a change rule of the area of each section of the diffuser along the central line. In the aspect of transition of the shapes of an inlet and an outlet of the diffuser, once the inlet section and the outlet section have been mapped to a ξ-η space, a plurality of transition shapes between the inlet section and the outlet section are obtained by using a matrix transformation-based improved algorithm. The shapes of the inlet and the outlet, and each transition shape jointly form the shape of each local section of the diffuser along the central line. On the basis of the shapes of the sections, the change rule of the sectional area, and the change rule of the central line, the final three-dimensional geometry of the diffuser can be constructed under an o-xyz three-dimensional coordinate system, and the three-dimensional geometric modeling of the diffuser can be flexibly and controllably designed.

A centroid and a plurality of points associated with a cuboid may form triangles to represent a portion of a point cloud, which represent an object or scene in content. Variations in the positions of points in the cuboid may shift the centroid's position, which may cause potential distortion. Optimizing the centroid's position, based on weighted points associated with the cuboid, may improve compression performance and rendering.

The invention discloses a necking detection method based on geometric feature self-adaption. The necking detection method comprises the following steps that S1, the longest main axis of a simulation graph is determined; s2, selecting N feature points on the longest main shaft; s3, obtaining the minimum key size of the simulation graph at each feature point; and S4, judging whether the simulation graph has a necking risk or not based on each minimum key size. By identifying the geometric centroid and the longest principal axis of a graph, adaptively selecting feature points and performing omnidirectional scanning, the measured minimum critical dimension is compared with a set safety threshold, and a risk point which is most likely to generate necking on the graph is accurately positioned, so that the automation and objectification of risk detection are realized, and the risk detection efficiency is improved. Subjectivity and experience dependence of manual marking are avoided, and consistency of detection results is guaranteed; meanwhile, the method has good adaptability to complex or deformed contours, missing detection and misjudgment are effectively avoided, and the yield and reliability of chip manufacturing are improved.

This invention provides a method for locating the centroid of weak targets based on curvature track preprocessing and improved Gaussian function fitting. The method includes detector noise correction and initial value calibration of the Gaussian function variance; extraction of feature points of the weak target; target track screening based on track association and clustering; and parameter estimation by substituting the initial value of the two-dimensional Gaussian function into the improved two-dimensional Gaussian fitting model, achieving sub-pixel-level accurate positioning of the centroid of the weak target. This invention can balance operating speed and target positioning accuracy, and calculate the centroid of moving weak targets in real time.

The application discloses a scaling method and device of a three-dimensional model, a storage medium, equipment and a program product, and comprises the following steps: scaling a three-dimensional model in a model coordinate system at a preset scaling ratio, wherein the origin of the model coordinate system is located at the centroid of the three-dimensional model; determining a first position coordinate of the centroid in a world coordinate system, wherein the first position coordinate comprises a first coordinate, and the first coordinate is used to represent the height of the centroid in the world coordinate system; scaling the first coordinate based on the preset scaling ratio to obtain a second coordinate; and adjusting a third coordinate of a second position coordinate of the scaled three-dimensional model in the world coordinate system based on the difference between the second coordinate and the first coordinate to obtain a target three-dimensional model, wherein the third coordinate is used to represent the height of the scaled three-dimensional model in the world coordinate system. The effect that the height of the centroid of the scaled three-dimensional model in the world coordinate system is consistent with that before scaling can be achieved, and the scaling processing efficiency is improved.

The invention discloses a curved surface flattening method and system for inhibiting size distortion of a specific area, a medium, equipment and a product in the technical field of computer graphics. The method comprises the following steps: rasterizing a narrow-band region A of a curved surface p1 to obtain 2 (k-1) triangular grids; fitting a space curve S1 according to the centroid coordinate points of all the triangular grids, uniformly sampling N points on the space curve S1, and vertically projecting each point to the triangular grid closest to the point as a projection point of the triangular grid; traversing all the triangular grids, and obtaining a mapping point set of the triangular grids according to projection points, closest to the specified end of the narrow-band region A, on the triangular grids; and sequentially rotating each triangular grid and the mapping point set thereof as a whole by utilizing a spatial transformation method under the condition of keeping the common edge and the common vertex of every two adjacent triangular grids coincide, keeping the normal vector directions of all the triangular grids after rotation to be the same, and completing curved surface flattening.

The invention provides an inertia tensor measurement optimal attitude angle solving method considering centroid offset, and belongs to the technical field of inertia tensor measurement. In order to solve the problem that when the true centroid of a measured rigid body does not coincide with a clamping reference point in traditional inertia tensor measurement, tiny deviation of an attitude causes a significant error, the method comprises the following steps: determining a rotation matrix of a rigid body coordinate system relative to a measurement coordinate system; according to the parallel axis theorem, obtaining an inertia tensor related to a measurement principle O; placing a measured object at a specified attitude angle, and obtaining an inertia tensor of the measured object in a measurement coordinate system; in any posture, a measured object is measured along three axes through the multi-point weighing platform and the torsional pendulum mechanism, and a linear model is established; on the basis of the Fisher information matrix, the optimal solution of the pitch angle of the measured body is obtained through D-optimal accurate measurement; and determining a value taking rule of a yaw angle and a final enforceable attitude set, and taking a fixed constant of the roll angle to obtain an optimal attitude angle.

A method of decoding from a bitstream a geometry of a point cloud is described. The point cloud is represented by a plurality of cuboid volumes. The plurality of cuboid volumes includes a plurality of occupied cuboid volumes being modelled by one or more triangles. The one or more triangles have vertices on edges of the occupied cuboid volume. The method includes decoding vertices located on edges of the occupied cuboid volumes, decoding a centroid residual per occupied cuboid volume, and refining vertices on one or more unique edges, which are shared by two or more of the occupied cuboid volumes, wherein the vertices are refined using the centroid residuals.

A method (100) for determining a dimension (D) of a mechanical part (PM1, PM2), comprising the steps of measuring (101) the position of points on an edge of the part's cross-section, determining (102) a skeleton curve (CSQ), comprising the steps of calculating (1021) a triangulation of the points of the cross-section curve (CS), and for each triangle of the triangulation, determining (1022) a center (CT) and a centroid (BT) of said triangle, filtering (1023) the centers (CT) based on the centroids (BT) to obtain a set of filtered centers (CTF), the determined skeleton curve (CSQ) comprising the set of filtered centers (CTF), and determining (103) the dimension (D) of the mechanical part at a skeleton point on the skeleton curve (CSQ) as a function of the position of said skeleton point on the skeleton curve (CSQ). Figure 2

A method for linearizing hydropower station output curves based on triangulation is proposed to address the technical challenge of linearizing three-dimensional output curves in reservoir optimal scheduling. This method first collects discrete data pairs of "head-generator flow-output" for hydropower station units, constructing a two-dimensional data list and an output list. Triangulation is then performed using the Delaunay function from the Python scipy library, generating a non-repeating triangular mesh, and constructing a dictionary containing the original data, the subdivision results, and data extrema. A mathematical model is then constructed, incorporating triangle selection constraints, centroid coordinate constraints, correlation constraints, and interpolation constraints, converting the nonlinear curve into a mixed-integer linear programming model. For scenarios with small variations in head and flow, calculations can be simplified by pre-setting envelope triangles. This invention eliminates the need for regular rectangular curves, significantly reduces binary variables, adapts to cascade reservoir group scenarios, and provides efficient solutions, offering reliable technical support for reservoir optimal scheduling.

The application belongs to the technical field of high-precision positioning, and particularly relates to a map element correlation matching method and system based on a centroid vector, which comprises the following steps: for two map element sets to be matched, a centroid vector matrix is constructed to record the relative position relationship between different types of elements in the set in the form of a vector; for a target element in the first set, a candidate element of the same type is searched for in the second set, a local candidate matching pair is generated by comparing the neighbor distribution similarity of the target element and each candidate element, and voting statistics are performed on all local candidate matching pairs to determine the final matching corresponding relationship according to the number of votes. The application can effectively resist spatial transformation, avoid cross-type mis-matching, and does not depend on a large amount of labeled data, and the matching process is clear and interpretable.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for aligning curves to precise geometric shapes using a geometry matching algorithm. For example, the disclosed systems generate a set of discrete points along a curve depicted in a digital image by sampling the curve spanning between a first corner and a second corner depicted in the digital image. The disclosed systems determine an order for comparing the set of discrete points with a first geometry and a second geometry by comparing a centroid of the curve with a centroid of the first geometry and a centroid of the second geometry. The disclosed systems also determine, according to the order, a first similarity of the curve to the first geometry and a second similarity of the curve to the second geometry. The disclosed systems generate curve segments that align with one of the first geometry or the second geometry.

The invention provides a dispensing method based on generation of a filling track on a curved surface. The method comprises the steps of obtaining a to-be-filled feature curved surface from a workpiece model, and generating an original three-dimensional triangular mesh; carrying out subdivision to generate a subdivided three-dimensional triangular mesh; unfolding to a two-dimensional plane to generate a two-dimensional triangular grid; generating a corresponding two-dimensional polygon according to the outer contour of the two-dimensional triangular mesh and the boundary of the inner hole; constructing a query structure, dispersing the generated two-dimensional filling track into two-dimensional track points, querying triangular positions where the two-dimensional track points are located in the query structure, and calculating corresponding barycentric coordinates; and calculating coordinates of three-dimensional filling track points of the filling track according to the one-to-one correspondence of the subdivided three-dimensional triangular grids and the two-dimensional triangular grids and the calculated barycentric coordinates, connecting the three-dimensional filling track points by using polygonal line segments to obtain a continuous three-dimensional filling track, and obtaining a final curved surface filling track.

The application discloses a kind of complex microstructure surface step height or groove depth uncertainty fast evaluation method, belong to optical measurement technical field.The application obtains the three-dimensional topography original measurement data of step or groove in integrated circuit complex microstructure surface, obtains effective three-dimensional topography matrix Z m With X, Y plane after dimension reduction, is decomposed into reconstruction matrix A and B, and the data point of corresponding row constitutes dot matrix;The centroid distance of data point in dot matrix after clustering of corresponding row is converted into step height or groove depth value;All row data are traversed, and the mean value of step height or groove depth value is regarded as key dimension representation result, and mean square error value is regarded as standard uncertainty;The representation value of all row data is arranged in ascending order, and the upper and lower limits of 95% confidence interval are regarded as key dimension uncertainty distribution range.The application can realize the step height or groove depth representation of all points of complex microstructure surface by once measurement, and simultaneously can realize uncertainty evaluation.

The application discloses a multi-modal open intention recognition method and system based on granular ball representation, and belongs to the technical field of artificial intelligence and multi-modal intention understanding, which comprises the following steps: performing feature extraction and mode fusion on multi-modal input data; performing structural modeling on the feature representation of each mode and the fusion mode by using a self-adaptive granular ball clustering method, and generating a multi-granularity granular ball set; taking the granular ball centroid as a multi-granularity anchor point, and aligning the granular balls with the same label in different modes; introducing a weighting mechanism based on purity and sample size in the fusion mode; generating boundary-constrained pseudo-distribution out-of-distribution samples in the fusion mode space; constructing a self-adaptive decision boundary based on the fusion mode granular balls obtained through training, and performing known class classification and unknown class detection. By introducing the multi-granularity anchor point and the structure-perception granular ball representation mode, the application realizes the joint recognition of known classes and unknown classes in a multi-modal scene, and significantly improves the accuracy and robustness of intention recognition.

A system is configured to: (a) provide a deep learning model; (b) receive a concept, the concept including text; (c) determine a word embedding representing the concept using the deep learning model; (d) determine a centroid for the concept, the centroid representing an average position of concept characteristics in a high-dimensional word embeddings space; (e) determine Euclidean distances for each of the concept characteristics; (f) determine cosine similarities for each of the concept characteristics; (g) determine a prominence index for each of the concept characteristics based on the determined Euclidean distances and the determined cosine similarities; and (h) provide, to a client device, a ranking of the concept characteristics based on the prominence index.

The application discloses a kind of space multibody system dynamics modeling method based on Lagrange multiplier method, first establish the coordinate conversion matrix of local to global coordinate system of each component in space;With centroid coordinates and Euler angle definition active component pose, determine generalized coordinate;Position constraint equation is established to kinematic pair, after first and second derivative, obtain the numerical expression of velocity, acceleration constraint equation;Through the cross product property of space angular velocity matrix and vector and the symmetry of vector cross product, the velocity constraint equation is converted, and the numerical expression of Jacobian matrix and time partial derivative term is obtained;Based on the modified Lagrange multiplier method, the cross product term of angular velocity and angular momentum of space component rotation is considered, the dynamics equation is established and solved;The correlation law of Euler angle and space angular velocity is established, the conversion of both is realized.Therefore, the method of the application is suitable for various space multibody systems, solves the problem of existing modeling method when dealing with complex constraints, fills the gap of prior art.

This invention proposes a relative center of mass measurement method to obtain the distance between the axial center of mass and the tip. Based on the three-point weighing method for center of mass measurement, this invention measures the product in a horizontal axial position by performing two measurements, one in the forward direction and one in the reverse direction. This transforms the direct measurement of the axial center of mass into the phase offset of the two measurements, thereby calculating the distance between the axial center of mass and the rotation axis. This distance is then combined with the distance between the rotation axis and the large end of the product to obtain the distance between the center of mass and the large end of the product. Based on this distance and the product length, the axial center of mass is obtained.

A decoding method includes: receiving a bitstream including geometry information and first control information, the geometry information indicating nodes constituting an octree structure, the first control information indicating whether a first face of a first node included in the nodes includes a first face vertex provided on the first face except for first edges of the first face; and generating or not generating the first face vertex on the first face according to the first control information. Each of the nodes is a unit for containing three-dimensional points. The first node includes a first centroid vertex and first edge vertices that are used in TriSoup scheme. The first face vertex, the first centroid vertex, and the first edge vertices define a triangle on which three-dimensional points in the first node are disposed. The first control information is provided for a face of the first node that satisfies a predetermined condition.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for aligning curves to precise geometric shapes using geometric matching algorithms. For example, the disclosed system generates a set of discrete points along a curve depicted in a digital image by sampling the curve across between a first corner point and a second corner point depicted in the digital image. The disclosed system determines an order for comparing the set of discrete points to the first geometry and the second geometry by comparing the centroid of the curve to the centroid of the first geometry and the centroid of the second geometry. The disclosed system also determines a first similarity of the curve to the first geometry and a second similarity of the curve to the second geometry according to the order. The disclosed system generates a curvilinear segment aligned with one of the first geometry or the second geometry.

The invention discloses a hierarchical multi-fragment point cloud splicing method based on geometric perception, and belongs to the technical field of computer vision. Aiming at the problems of limited feature representation capability and insufficient splicing precision in the existing method, the method comprises the following steps: firstly, extracting local geometric features by using DGCNN, and meanwhile, fusing relative positions of centroids to construct multi-dimensional feature representation so as to improve the recognition quality of fracture points; secondly, a staged strategy is designed to achieve fine matching, rough matching based on global shape similarity and fine matching based on local geometric affinity are combined, and matching ambiguity is effectively reduced; finally, an auxiliary transformation estimation mechanism based on the geometric center of the fracture point cloud is provided and used for stably initializing attitude parameters, and therefore the alignment precision and the convergence stability are improved at the same time.

The application discloses a fitting method and device of a space circle track and a computer readable storage medium. The fitting method comprises the following steps: acquiring a plurality of collection data points in a three-dimensional space; performing plane fitting based on the plurality of collection data points to obtain a target plane; calculating the centroid of the plurality of collection data points; determining the center of a target circle according to the centroid; determining the radius of the target circle according to the distance from the center of the target circle to the plurality of collection data points; determining a target sphere space with the center of the target circle as the center of a sphere and the radius of the target circle as the radius of the target sphere; and determining the target circle track according to the target plane and the target sphere space. The fitting method provided by the application can improve the fitting accuracy of the space circle track.

A method of decoding from a bitstream a geometry of a point cloud is described. The point cloud is represented by a plurality of cuboid volumes. The plurality of cuboid volumes includes a plurality of occupied cuboid volumes being modelled by one or more triangles. The one or more triangles have vertices on edges of the occupied cuboid volume. The method includes decoding vertices located on edges of the occupied cuboid volumes, decoding a centroid residual per occupied cuboid volume, and refining vertices on one or more unique edges, which are shared by two or more of the occupied cuboid volumes, wherein the vertices are refined using the centroid residuals.

The present disclosure relates to systems, non-temporary computer-readable media, and methods for aligning curves to precise geometric shapes using a geometry alignment algorithm. The disclosed systems, for example, generate a set of discrete points along a curve represented in a digital image by scanning the curve extending between a first vertex and a second vertex represented in the digital image. The disclosed systems determine an arrangement or sequence for comparing the set of discrete points with a first geometry and a second geometry by comparing a centroid of the curve with a centroid of the first geometry and a centroid of the second geometry. The disclosed systems also determine, according to the arrangement or sequence,The sequence involves a first similarity of the curve to the first geometry and a second similarity of the curve to the second geometry. The disclosed systems generate curve segments that are aligned with either the first or the second geometry.

The application discloses a kind of three-dimensional target detection methods based on class enhancement and geometric enhancement, the method first input laser point cloud, random sampling to 16k points, carries out two furthest point sampling and ball query in succession, obtains 2048 center points.Secondly, to 2048 center points, by class enhancement multiple sampling module carries out two sampling and ball query in succession, obtains two center points, and its corresponding multi-scale aggregation feature 3 and multi-scale aggregation feature 4.Then to multi-scale aggregation feature 4 using MLP predicts centroid shift, so that each point is shifted to centroid, and then using geometric enhancement centroid attention module, obtains the centroid feature of centroid point.Finally, using centroid feature carries out object classification, and predicts object bounding box 3D position, size and direction, and eliminates overlapping bounding box.The application reduces missed detection and improves overall detection performance, and remarkable improvement is achieved in distant object detection.