178 results about "Transformation matrix" patented technology

The invention relates to the technical field of face verification, and discloses a face identity verification data processing method based on dynamic feature extraction, which comprises the following steps: acquiring a continuous face video frame sequence and calculating a full-pixel instantaneous velocity vector to generate an original dense optical flow field, selecting rigid region anchor points to calculate a rigid affine transformation matrix and construct a theoretical rigid motion field, performing differential stripping on the theoretical rigid motion field from the original dense optical flow field, and extracting a non-rigid micro-motion residual field; mapping the non-rigid micro-motion residual field to a facial muscle topological grid to generate a time sequence feature tensor, and calculating a geodesic line distance between a covariance matrix of the time sequence feature tensor and a reference dynamic feature in a Riemannian manifold space; when the geodesic distance is smaller than a threshold value, verification is passed, through a rigid-non-rigid orthogonal decomposition mechanism, the special viscoelastic micro-motion and cooperation law of biological soft tissue is captured by utilizing a residual field, and the high-simulation mask is effectively defended.

The invention relates to the technical field of industrial vision and intelligent monitoring, and discloses a loom control system operation state monitoring and fault diagnosis method based on machine vision, which comprises the following steps: acquiring a video stream in a loom shed area and constructing a two-dimensional space-time slice tensor; performing global motion compensation processing on the space-time slice tensor by using a homography transformation matrix, mapping a compensated dynamic texture feature sequence to a three-dimensional phase space by using a time delay embedding algorithm, and reconstructing a closed phase space trajectory representing periodic operation logic of the loom; the discrete Frechet distance between the phase space trajectory of the current operation cycle and the preset reference trajectory is calculated, and a control instruction is generated. The health degree of the sequential logic of the system is directly quantified on the premise that specific components are not recognized by using the invariant characteristic of the phase space manifold topology; the technical problems that small phase lag is difficult to perceive and nonlinear faults cannot be early warned in a strong noise environment are solved.

The embodiment of the invention discloses a point cloud registration method and system and electronic equipment. The method comprises the following steps: performing height layering on a source point cloud and a target point cloud in a preset height range to obtain a plurality of point cloud layers; performing feature matching based on each point cloud layer of the source point cloud and each point cloud layer of the target point cloud, and determining a plurality of reference transformation matrixes; performing consistency voting screening on the rotation components of the plurality of reference transformation matrixes to obtain at least one candidate transformation matrix; performing block verification on the source point cloud and the target point cloud according to the at least one candidate transformation matrix to determine an optimal transformation matrix; and performing fine registration based on the optimal transformation matrix, and determining a final transformation matrix of the source point cloud and the target point cloud according to a fine registration result. According to the technical scheme, point cloud map registration can be rapidly and accurately completed without an initial pose, and the problems of low speed, low precision and poor robustness of large-scale point cloud registration in the prior art are solved.

The invention belongs to the technical field of data processing, and particularly relates to a multi-view cloud high-precision fusion splicing method based on semantic geometry collaborative optimization, which comprises the following steps: extracting and quantifying features of multi-view cloud, endowing each point cloud with a semantic label, calculating the confidence coefficient of classification of each point cloud, and simultaneously calculating the normal vector and curvature geometric features of each point cloud. And performing robust initial registration based on semantic constraint, and outputting a robust initial transformation matrix. And constructing a collaborative energy function, carrying out dynamic quantitative coupling on semantic confidence and geometric stability, and carrying out iterative registration. And realizing anisotropic point cloud fusion based on semantic guidance, and outputting a fused and spliced three-dimensional point cloud model. And finally, verifying the performance of the method, and measuring fusion splicing errors. According to the method, the semantic features of the point cloud data are effectively extracted and utilized, the precision and robustness of point cloud fusion splicing are improved, and geometric details of a final model are reserved to the maximum extent.

The invention provides a video point cloud data fusion and curved surface reconstruction method based on a digital twin scene, and belongs to the technical field of video processing. Then, inertial data is mapped to a Lie group manifold space, and a continuous trajectory model is constructed by using B spline fitting; based on the model, accurately calculating a first pose transformation matrix at the exposure moment of each row of pixels and a second pose transformation matrix of each laser point; then, projecting the point cloud to a global coordinate system by using the second matrix, and generating multi-dimensional feature mapping data of space-time registration by combining the first matrix, the internal reference and a perspective principle; and finally, inputting the data into a voxelization truncated symbol distance field, synchronously updating a distance value and a color weight, and generating a high-fidelity digital twin three-dimensional curved surface by extracting a zero level set contour surface.

This invention relates to the field of image recognition technology, specifically providing a multi-view point cloud registration method. In the coarse registration stage, the RANSAC algorithm is used to perform coarse registration of the source and target point clouds based on multi-dimensional features, obtaining a coarse registration transformation matrix. In the fine registration stage, the coarse registration transformation matrix is ​​used as the initial value, and point cloud registration is performed in at least two resolution spaces. Segmented iterative optimization is performed using an error loss function set for each resolution space. In the low-resolution space, an iterative nearest-point algorithm is used for rapid convergence, while in the remaining resolution spaces, a generalized iterative nearest-point algorithm is used for local geometric alignment optimization. After progressive optimization registration in multiple resolution spaces, the fine registration of the source and target point clouds is completed. This invention significantly improves the robustness of feature matching in low-overlap regions, balances registration speed and accuracy, and overcomes the limitations of traditional point cloud registration methods under low-overlap and non-ideal point cloud conditions.

The invention discloses a feature selection method and a data reconstruction method for shoreline image feature selection. The method comprises the following steps: S1, integrating original data into a sample data set matrix X; s2, initializing a reconstruction transformation matrix W, a transformation matrix Q, an eigenvalue regression coefficient matrix A, a coordinate basis matrix B, a coding matrix E, an auxiliary matrix F and an auxiliary matrix D as unit matrixes, initializing a weight vector p and a mean vector v of a data set as unit vectors, and initializing a weight matrix P = diag (p); and S3, updating the coding matrix E, the auxiliary matrix F and the like based on the data set matrix X, the mean vector v of the data set, the transformation matrix Q, the eigenvalue regression coefficient matrix A, the coordinate basis matrix B and the weight matrix P. According to the invention, the accuracy of data reconstruction and the validity of feature selection can be improved.

The invention discloses a three-dimensional scene reconstruction method and system for an energy storage battery cabin. The method comprises the following steps: carrying out geometric reconstruction on acquired multi-view image data by using camera calibration parameters; projecting the initial three-dimensional point cloud to an imaging plane of a reference visual angle to obtain a priori depth map DCi; performing depth filling processing on the priori depth image DCi and the reference view ICi by using an image-guided depth filling algorithm; plane constraint depth optimization processing is carried out on the depth map DCi '; converting the depth map DCi ''into point cloud data, and performing feature extraction on the point cloud data by using an FPFH algorithm; performing first registration on the point cloud data and the point cloud data of other visual angles through an RANSAC algorithm to obtain a registered initial transformation matrix; carrying out the second registration of the point cloud data after the initial transformation matrix through an ICP algorithm, and obtaining a final transformation matrix; according to the invention, the multi-view point cloud fusion precision is improved.

The invention belongs to the technical field of computer vision and three-dimensional image processing, and particularly discloses a mismatching mark point correction method and system based on an improved RANSAC algorithm. According to the method, congruent triangle criteria are introduced into the RANSAC algorithm, and potential matching point pairs conforming to geometric consistency are screened. Only when the potential matching point pairs meet the geometric consistency, the transformation matrixes R and T are solved, that is, mismatching points existing in the potential matching point pairs are effectively eliminated, so that on the premise that the point cloud splicing precision and the success rate are not changed, wrong calculation is reduced, the point cloud registration efficiency and robustness are improved, and the point cloud registration accuracy is improved. The method is suitable for various application scenes such as industrial part measurement, medical modeling, cultural relic digital protection and virtual reality.

The invention relates to the technical field of computer graphic processing, and discloses a method for automatically drawing a DCS (Distributed Control System) picture into a real-time database picture, which comprises the following steps of: firstly, identifying a DCS source file format, directly analyzing a public text format or intercepting a bottom layer rendering instruction for a private binary format, and extracting standardized discrete data; constructing an intermediate vector model, and performing coordinate normalization and curve smoothing processing on the static primitives by using an affine transformation matrix; meanwhile, syntactic analysis is conducted on the control script to construct an abstract syntax tree, and dynamic logic is converted; then recombining a composite object based on spatial semantics, and repairing pipeline topology connection by utilizing automatic adsorption and an orthogonal routing algorithm; and finally, calling a target system interface to complete object instantiation and persistent storage. According to the invention, the automatic high-fidelity migration of the DCS picture to the real-time database is realized, the labor cost is reduced, and the consistency and accuracy of the monitoring picture are ensured.

The present invention provides a projection device, a projection method, and a measurement device that are for assisting measurements performed by a three-dimensional measurement machine. This projection method comprises: a step for acquiring a transformation matrix for performing coordinate transformation from a coordinate system of a measurement device (10) to a coordinate system of a projection device (50); a step for using the transformation matrix to perform coordinate transformation to the coordinate system of the projection device with respect to a measurement assistance image in which the shape of a measurement target area of a workpiece that has been installed in the measurement device is indicated by the coordinate system of the measurement device; and a step for projecting the coordinate-transformed measurement assistance image onto the workpiece.

This application discloses a fast and interpretable homography decomposition method, relating to the field of computer vision technology. The method includes: obtaining a first anchor point pair, a second anchor point pair, and two sets of auxiliary point pairs based on a source image and a target image; calculating a first similarity transformation matrix based on the first anchor point pair and a second similarity transformation matrix based on the second anchor point pair; the first similarity transformation maps the first anchor point pair to a standard anchor point, and the second similarity transformation maps the second anchor point pair to the standard anchor point; calculating the parameters of a kernel transformation matrix using the auxiliary point pairs on the source plane and the target plane; the kernel transformation matrix has the property of preserving the standard anchor points; and synthesizing a homography matrix from the source plane to the target plane based on the first similarity transformation matrix, the second similarity transformation matrix, and the kernel transformation matrix. This application aims to solve the problems of low computational efficiency, scene limitations, and lack of algebraic and geometric meaning in existing homography calculation methods.

This invention discloses a method, system, device, and storage medium for generating three-dimensional cutting trajectories, comprising the following processes: acquiring a CAD model of the finished product, extracting cutting trajectory lines, and generating a three-dimensional point cloud of the CAD model; scanning the workpiece to be cut to generate a three-dimensional point cloud of the workpiece; registering the three-dimensional point cloud of the CAD model and the three-dimensional point cloud of the workpiece to be cut, calculating the transformation matrix, and performing coordinate system transformation on the CAD model according to the transformation matrix; generating a set of cutting poses based on the cutting trajectory lines and the transformation matrix, performing translation and rotation adjustments, smoothing, sorting, deformation compensation, and robot kinematics checks on the set of cutting poses to generate a set of cutting trajectories containing multiple cutting trajectories; and generating a cutting program based on a recognizable syntax based on the set of cutting trajectories containing multiple cutting trajectories.

This invention relates to a method, apparatus, device, and medium for error compensation in a dual-drive feed system, belonging to the field of CNC equipment error measurement and compensation technology. The method includes: establishing a low-order volume array of the equipment to be modeled, equipped with a dual-drive feed system; obtaining an error transmission chain from the workpiece to the tool based on the low-order volume array; establishing a mathematical model of tool error and dual-axis error when the dual axes of the dual-drive feed system drive the tool; determining the homogeneous coordinate transformation matrix between any two volumes in the low-order volume array; establishing an error transmission matrix from the workpiece coordinate system to the tool coordinate system based on the error transmission chain, mathematical model, and homogeneous coordinate transformation matrix; establishing a comprehensive error model of the dual-drive feed system based on the error transmission matrix and the transmission matrix under ideal conditions; and performing error compensation on the dual-drive feed system based on the comprehensive error model, thereby improving the error compensation accuracy of the dual-drive feed system.

The invention relates to an implementation method for applying linear subcomponents of a ZUC algorithm to multiple scenes. The method comprises the following steps: constructing a linear transformation matrix expression from an input bit sequence to an output bit sequence of a linear subcomponent according to the definition of the linear subcomponent in the ZUC algorithm; and carrying out structure division on the linear transformation matrix expression, and decomposing the original large-scale matrix operation into at least two independent small-scale matrix operations. And according to each small-scale matrix design, a logic gate level implementation scheme based on in-situ XOR operation is designed, and a bit operation sequence is generated. And mapping the logic gate-level implementation scheme into a plurality of physical circuit modules with a hierarchical connection relationship according to the data dependency relationship among the bit operation sequences, so that all the physical circuit modules jointly form a component structure suitable for multiple scenes. By adopting the method, the reliability and applicability of the communication system or equipment for executing the ZUC algorithm can be enhanced.

The application discloses a master-slave manipulator coordinate position follow-up control method and system based on machine learning, comprising the following steps: step one: establishing a two-way data acquisition and execution architecture of the master-slave manipulator; step two: performing resampling processing, reading a calibration transformation matrix for matrix combination, and calculating multi-dimensional motion characteristics; step three: performing prediction operation through an improved Crossformer model; step four: solving initial target angles of each joint and jointly correcting the target joint trend quantity; step five: calculating joint self-weight torques T1 in an empty load state and joint comprehensive torques T2 in a load state; step six: generating a driving compensation quantity corresponding to a direction of the master manipulator and a master-slave coupling feedback sequence; and step seven: constructing an error characteristic matrix and compressing and mapping the error characteristic matrix into an error guide vector. The application realizes accurate follow-up and force feedback of the master-slave manipulator through the improved Crossformer model.

The invention relates to the technical field of robot obstacle avoidance, and discloses a robot obstacle avoidance method and device based on dimension reduction motion parameters, and a storage medium, and the method comprises the steps: recording an initial motion track of an obstacle when it is monitored that the obstacle appears in a target working region, and fitting the initial motion track into an initial motion parameter matrix under a robot working coordinate system; acquiring a local base coordinate transformation matrix containing a rotation parameter variable and a non-orthogonal parameter variable; performing multi-round assignment on the rotation parameter variable and the non-orthogonal parameter variable, after each round of assignment, transforming the initial motion parameter matrix into a transformed parameter matrix by using the obtained local base coordinate transformation matrix, performing sparse processing, calculating a sparse parameter matrix, and determining a target rotation parameter and a target non-orthogonal parameter according to the sparse parameter matrix; representing the target rotation parameter, the target non-orthogonal parameter and the corresponding sparse parameter matrix as dimension reduction parameters; and representing a motion track of the predicted obstacle according to the dimension reduction parameter, and generating a robot avoidance path based on the motion track.

This invention relates to image registration methods, specifically to an infrared and visible light image registration method. It addresses the problem that existing infrared and visible light image registration methods cannot simultaneously achieve both efficiency and accuracy. This invention first acquires multiple sets of visible light images and corresponding infrared images of a target at different distances, and processes them using the SIFT operator and RANSAC algorithm. A table is then created to record the transformation matrix from the infrared image to the visible light image at different distances. Subsequently, the visible light image to be registered and the corresponding infrared image are input into a trained convolutional neural network for processing. The output is the shooting distance values ​​of the visible light and infrared images to be registered. The corresponding transformation matrix is ​​obtained by looking up the table, and the infrared and visible light images are registered using this transformation matrix. The RANSAC algorithm is used to remove mismatched feature points, and combined with the distance prediction accuracy of the convolutional neural network, the accuracy of the transformation matrix is ​​doubled. Because of the pre-established table, feature point matching and matrix calculation are not repeatedly performed on each frame of the image, significantly improving the registration speed.

The invention provides a head image spatial registration method and device, equipment and a storage medium, and the method comprises the steps: extracting first facial feature points from a head three-dimensional model, and obtaining a first facial feature point set of a target object; extracting second facial feature points from the three-dimensional point cloud data of the face of the target object to obtain a second facial feature point set of the target object; determining a first rigid body transformation matrix based on the first facial feature point set and the second facial feature point set; performing coordinate transformation on the head three-dimensional model by using the first rigid body transformation matrix; determining a second rigid body transformation matrix based on the head three-dimensional model after coordinate transformation; determining a spatial transformation matrix according to the first rigid body transformation matrix and the second rigid body transformation matrix; and transforming the image data from the image coordinate system to a physical coordinate system where the head of the target object is located based on the spatial transformation matrix. By adopting the technical scheme provided by the invention, the registration precision and the registration efficiency are improved.

The present application relates to the technical field of feature vector merging in large model inference acceleration, in particular to a feature vector similarity measurement method and device based on transformation domain, by constructing a new type of calculation path of "transformation-measurement", using an orthogonal transformation matrix to project the feature vector to the transformation domain and then calculating the absolute value error sum, effectively extracting the internal structured features, solving the defect of insufficient accuracy of traditional lightweight measurement indicators, designing a multiplierless hardware acceleration architecture supporting the algorithm, by strictly constraining the element values of the orthogonal transformation matrix within the integer set of {-1, 0, 1}, completely equivalent to the matrix multiplication into simple addition and subtraction operation, completely avoiding multiplication, division and square root operation, greatly reducing the chip area and power consumption overhead, in addition, the pareto optimality of model accuracy and hardware efficiency is also realized, and the configuration capability of searching and customizing the transformation matrix for specific models is also provided.

The application provides a power meter correction electric quantity calculation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring metering history data of a target power meter; analyzing the metering history data by using a phase angle feature portrait algorithm, and identifying a wiring error type corresponding to the target power meter; determining a corresponding correction transformation matrix based on the wiring error type; and calculating the correction electric quantity of the target power meter based on the correction transformation matrix. The application provides a novel power meter correction electric quantity calculation scheme. By using an advanced algorithm and a mathematical model, the correction electric quantity of the power meter can be more accurately calculated, the interference of human factors is reduced, various complex wiring error conditions can be adapted to, and therefore the accuracy and reliability of the power system power meter correction electric quantity calculation method are improved.

The invention discloses a ship backside completion method based on dynamic screening and registration optimization of a medial plane, and belongs to the technical field of three-dimensional point cloud data processing. The method comprises the following steps: step 1, carrying out dynamic adaptive statistical filtering noise reduction on an input original point cloud, dynamically adjusting a neighborhood size and a threshold value according to a local point cloud density, and adaptively distinguishing noise and effective points; step 2, screening out a medial surface according to different ship types, and optimizing the medial surface; 3, generating back-side missing data from the complete front-side point cloud data through symmetric mapping by using the inherent symmetry of a ship structure; step 4, through quantitative analysis of the spatial matching degree between the completion point cloud and the original point cloud, screening out a completion result closest to the real geometric distribution; step 5, performing registration based on the optimal completion point cloud screened out in the step 4 to obtain a point cloud alignment result; and step 6, optimizing and adjusting the medial surface by using the transformation matrix obtained by ICP registration so as to approach the real medial surface of the ship.

This application relates to the field of image data processing technology, and in particular to an image enhancement method based on video IP frames. The method includes: acquiring a target video V; parsing V to obtain a list L of frame numbers corresponding to keyframes in V; sequentially traversing V, and if q matches a certain id in L... m If they are equal, then v is obtained using the first sub-model in the trained target neural network model. q Transformation matrix T q and T q The latest transformation matrix T is determined. new , will T q As input to the second sub-model in the trained target neural network model, the output of the second sub-model in the trained target neural network model is used as v. q The corresponding enhanced image; otherwise, T new As input to the second sub-model in the trained target neural network model, the output of the second sub-model in the trained target neural network model is used as v. q The corresponding enhanced image. This invention improves the efficiency of image enhancement for videos.

Implementations disclosed describe techniques used for compiling a quantum algorithm for execution on a plurality of quantum circuits, including accessing, by a processing device, the quantum algorithm, identifying a matrix associated with the quantum algorithm, determining a representation of the identified matrix as a matrix decomposition that includes a plurality of transformation matrices, wherein one or more of the plurality of transformation matrices perform multiple instances of two-dimensional rotations; and generating a circuit map that maps execution of the matrix decomposition on the plurality of quantum circuits.

Systems and techniques are described for image processing. For example, a computing device can determine feature points in a first image and can determine motion vectors associated with the feature points. The computing device can determine background motion vectors associated with a background of a scene of the first image. The computing device can determine, based on the background motion vectors, a transformation matrix for aligning the backgrounds of the first image and a second image. The computing device can determine a scaling factor based on a magnitude of motion vectors within a portion of a foreground of the scene of the first image and can scale, based on the scaling factor, the transformation matrix to generate a local transformation matrix for aligning the portion of the foreground of the scene of the first image with a corresponding portion of the foreground of the scene of the second image.

The invention relates to a coordinate processing method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a first coordinate point set corresponding to a target point in a programming coordinate system, and obtaining a second coordinate point set corresponding to the target point in a preset actual coordinate system; performing transformation parameter calculation on the first coordinate point set and the second coordinate point set based on a least square method to obtain an initial transformation matrix; calculating the initial transformation matrix based on an error function to obtain an error value; if the error value is greater than an error threshold value, optimizing the initial transformation matrix by using a random sampling consensus algorithm based on the first coordinate point set and the second coordinate point set to obtain a first transformation matrix; performing iterative optimization on the first transformation matrix based on an iterative nearest point algorithm until an iteration termination condition is met, and obtaining a target transformation matrix; and performing coordinate transformation on the first coordinate point set based on the target transformation matrix to obtain a corresponding target coordinate point set. According to the invention, the precision of coordinate conversion can be effectively improved.

The application discloses a kind of based on deep learning's drawing comparison method, comprising: obtaining first image based on original drawing and second image formed based on original drawing scanning;According to key point extraction, matching algorithm, reliable key point matching pair is obtained by first image and second image, and perspective transformation matrix is calculated according to reliable key point matching pair, and second image is aligned to first graph according to perspective transformation matrix, and reprojected second image is obtained after alignment;According to difference comparison model, difference prediction is carried out to first image and reprojected second image, and difference image is obtained;Difference block confirmation image is obtained by dividing difference image according to predetermined parameter, and finally difference confirmation is completed by user;It is more accurate to achieve for small difference capture and noise caused misjudgment processing, suitable for various drawing comparison, especially for drawing quality difference, and better results can be predicted.

The application provides a loop detection method and system based on a semantic ellipsoid, performs target detection, and obtains a preliminary ellipsoid model by constraining semantic point clouds obtained through target detection on a key frame; in subsequent observation, the model is continuously optimized through detection frame constraint and a nearest neighbor relationship semantic histogram is updated as a descriptor; in loop detection, optimal matching is performed on the current local semantic graph and global map semantics based on descriptor similarity and geometric consistency, a transformation matrix of the local graph to the global map is calculated according to the matching result, a loop matching mechanism is established based on inliers, and the map loop is corrected. The application extracts semantic information in a scene through target detection, obtains a scene semantic graph through ellipsoid modeling and optimization, and realizes loop detection based on map semantic matching suitable for large visual angle differences.

The invention discloses a casting head cutting and grinding NC program generation method and system, and relates to the technical field of intelligent control, and the specific steps are as follows: obtaining a machine tool reference coordinate system, associating a feeding motion coordinate axis, a workpiece pose axis and a cutter pose axis with a set axis of a machine tool control system based on the machine tool reference coordinate system, and according to a casting three-dimensional mathematical model, generating a casting head cutting and grinding NC program; defining key parameters by taking a process step as a unit, and generating an initial preset NC code covering the whole process characteristics; based on the obtained point cloud data of the workpiece in the current working step, the installation pose error of the installed workpiece is recognized, and a coordinate transformation matrix T from a workpiece coordinate system to a machine tool reference coordinate system is solved; and converting the coordinate of the key reference point on the mounting workpiece to the reference coordinate system of the machine tool by using the coordinate transformation matrix T, and updating the initial preset NC code based on the converted coordinate of the key reference point. The machining preparation time is shortened, and the automation degree and the overall efficiency of cutting and grinding of the casting head of the complex casting are improved.