72 results about "Angular point" patented technology

The invention provides a three-dimensional calibration method using a speckle image as a calibration object and combining weight parameters. The method comprises the following steps: acquiring a standard grid image and the speckle image through a camera; determining angular point positions in the standard grid image through an angular point detection algorithm; calibrating the stereoscopic vision system by using the obtained angular points to obtain an initial calibration result; calculating 3D coordinates of the camera calibration board in the world by using the disparity map; determining a subset of the reference image corresponding to the checkerboard angular points in the target image through a digital image cross-correlation algorithm; calculating a weight parameter of each calibration point based on the re-projection error; solving internal and external parameters of the camera by using the weight parameters, radial alignment constraint and a least square method; optimizing the main point of the camera by using the weight parameters; and if the re-projection error or the number of iterations does not meet the requirement, repeatedly calculating the weight parameter of the calibration point and the subsequent steps, otherwise, obtaining a camera calibration result, and obtaining the distortion curved surface of the camera lens.

The invention relates to the technical field of object recognition based on image and point cloud fusion, and discloses a machine vision-based obstacle detection method and system in a container moving process, and the method comprises the steps: obtaining three-dimensional point cloud data through a laser radar installed on container carrying equipment, and obtaining a two-dimensional image through an industrial camera; performing terrain reference correction on the three-dimensional point cloud data, and establishing an inclined coordinate system matched with the ground gradient; performing perspective distortion correction on the two-dimensional image based on the inclined coordinate system to obtain a corrected two-dimensional image; extracting edge features, angular point features and semantic features from the corrected two-dimensional image; extracting geometric features and reflection intensity features of the three-dimensional point cloud data under the inclined coordinate system; performing cross-modal fusion on the edge features, the angular point features, the semantic features, the geometric features and the reflection intensity features to generate fusion features; and the obstacle type is identified based on the fusion feature, and the obstacle sensing reliability in the complex industrial environment is improved.

The invention relates to the technical field of SLAM, in particular to a dynamic environment robust positioning method based on improved ORB-SLAM2, and the method comprises the steps: obtaining RGB-D scene data containing an indoor moving object, and extracting ORB feature points described by FAST angular points and BRIEF descriptors; extracting feature points with unreliable heights according to geometric features of ORB feature points of adjacent frames; pixel analysis is carried out on the RGB-D scene data based on a Fast-SAM instance segmentation model, and a mask matrix containing environmental object space boundary information is generated; performing point-prompt extraction on the height unreliable feature points and the mask matrix to obtain a dynamic object mask; removing ORB feature points existing in the dynamic object mask to obtain a reliable feature point set; and calculating matching point pairs in the reliable feature point set to obtain an essential matrix and a corresponding rotation matrix and translation vector, and refining the pose based on a nonlinear optimization method.

The invention discloses a camera calibration method and device, equipment and a storage medium. The method comprises the following steps: acquiring a first image acquired by shooting a calibration plate by a camera; wherein the calibration plate comprises a plurality of angular points; performing inverse perspective transformation on the first image based on the internal reference and the initial external reference of the camera to obtain a second image; detecting angular points in the second image to obtain a first angular point detection result; based on the first corner detection result, the first image and the internal reference, solving to obtain a target external reference of the camera; and calculating an error parameter based on the target external parameter, the internal parameter and the first image, and when the error parameter satisfies a preset condition, determining that camera calibration is completed. According to the technical scheme of the invention, the inverse perspective transformation is carried out on the first image shot and collected by the calibration plate, so that the influence of partial camera distortion can be eliminated, the accuracy of angular point detection is improved, and the success rate and accuracy of camera calibration can be improved.

Systems and methods are described relating to pose and shape estimation of objects. In some examples, a camera generates images depicting an object from different viewpoints. Within the images, a system identifies corners of the object, and the system uses these corners to generate lines that are projected from different viewpoints through the corners. Points may be identified by intersecting lines such that the points may be used to generate estimations of the object. The estimation with the highest score may be used to place the object in a location different from where the object was located.

The invention discloses an article grabbing and positioning method, system and device and a medium, and relates to the technical field of visual recognition. The method comprises the steps that a two-dimensional image, collected through a monocular camera, of an object to be grabbed is acquired; the types and the number of the to-be-grabbed articles in the two-dimensional image are recognized, and standard physical sizes corresponding to the types are determined; if the object is a single object, the object serves as a target to-be-grabbed object, the top face corner pixel coordinates of the object are detected, and the three-dimensional pose is solved through the PnP algorithm by combining the physical size and the internal reference of the monocular camera; if the number of the objects is multiple, all candidate corner points are detected, quadrilateral corner point sets of all the objects are screened out through clustering and geometric constraint analysis, then candidate three-dimensional poses of all candidate objects to be grabbed are calculated through a PnP algorithm, and then a target object to be grabbed is selected according to the candidate three-dimensional poses; and finally outputting the three-dimensional pose information of the target to-be-grabbed object. According to the invention, accurate positioning of a single article and three-dimensional pose recognition in a multi-article stacking scene are realized only by means of the monocular camera.

The present invention discloses a method and device for extrinsic parameter calibration based on a calibration template, comprising: collecting an RGB image and a depth map of the calibration template; aligning the RGB image and the depth map, and extracting inner corners of the RGB image based on a corner extraction algorithm; obtaining depth information corresponding to each inner corner point extracted from the RGB image on the depth map, and calculating the coordinates of each inner corner point in the camera coordinate system based on each inner corner point and its corresponding depth information; obtaining the coordinates of each inner corner point in the forklift coordinate system based on the relationship that the projection of a preset inner corner line of the calibration template coincides with the origin of the forklift coordinate system; and calculating the calibration extrinsic parameters of the camera based on the coordinates of each inner corner point in the camera coordinate system and the coordinates in the forklift coordinate system. The present invention solves the technical problems in the prior art of the complex calibration process of the calibration template and the low accuracy and robustness of the extrinsic parameter calibration.

The invention provides a vSLAM and display screen coordinate system alignment method and system based on a two-dimensional code, and the method comprises the steps: controlling a display screen to synchronously display a two-dimensional code with a known physical size and a known position parameter under a display screen coordinate system, collecting an image frame containing the two-dimensional code, and obtaining a camera pose synchronized with the image frame in time; identifying the two-dimensional code, extracting the coordinate of the angular point image, and calculating the spatial pose of the two-dimensional code in a vSLAM world coordinate system in combination with the physical size of the two-dimensional code participated in the camera; establishing a coplanar consistency constraint based on a plurality of two-dimensional code space poses, jointly estimating a display screen world pose of the display screen in a vSLAM world coordinate system, and calculating a deformation parameter used for representing a non-ideal plane state of the display screen; and further constructing a coordinate system mapping relation between a display screen coordinate system and a vSLAM world coordinate system, realizing accurate mapping from a screen coordinate to a world coordinate, and performing verification and exception processing on an alignment result.

The application relates to an object positioning method, device, system, readable storage medium and program product. The method comprises the following steps: acquiring an object angle range and an object edge direction vector of a target object; extracting at least one candidate corner point and at least one candidate edge line segment combination from a shooting image corresponding to the target object; extracting at least one candidate geometric feature combination from all candidate corner points and all candidate edge line segment combinations according to the object angle range and the object edge direction vector; screening a target object shape from a candidate object shape corresponding to each candidate geometric feature combination, and positioning the target object according to the target object shape. The method can accurately position the object.

The application provides a kind of slope surface displacement monitoring method, device, medium and equipment, comprising: collecting multiple image data of target slope;By analyzing multiple image data, determine multiple target targets and get the area code and pixel coordinates corresponding to the target target;Get the spatial coordinates of the four corner points of each target target in multiple target targets and the centroid coordinates of each target target;Respectively for each target target in multiple target targets, according to the spatial coordinates and centroid coordinates of the target target, the diagonal vector of each target target is calculated, the direction vector of the plane of each target target is obtained, and the direction vector has 3 direction degrees of freedom;The target slope is monitored by pixel coordinates, spatial coordinates, centroid coordinates and direction vector, and the monitoring result is obtained;Compared with the prior art, 3 displacement degrees of freedom + 3 direction degrees of freedom monitoring of the target slope is realized, and the precision of slope monitoring is improved.

The invention is suitable for the technical field of lasers, and provides a distortion correction method and device for an ultra-wide-angle camera and electronic equipment, and the method comprises the steps: obtaining a to-be-corrected image corresponding to a to-be-engraved material collected by the ultra-wide-angle camera in a laser engraving machine; distortion correction parameters corresponding to the ultra-wide-angle camera are obtained, the distortion correction parameters comprise a distortion coordinate matrix and a standard coordinate matrix corresponding to each angular point in a reference image, and the reference image is a calibration plate image collected by the ultra-wide-angle camera; and correcting the to-be-corrected image according to the distortion coordinate matrix and the standard coordinate matrix to generate a corrected image corresponding to the to-be-engraved material. Therefore, each pixel point in the to-be-corrected image is corrected to the correct position according to the pre-stored distortion correction matrix and the standard coordinate matrix, and image distortion generated during shooting of the ultra-wide-angle camera is eliminated, so that the image quality of the engraving breadth is improved, and the engraving precision of the laser engraving machine is improved.

The invention discloses a camera calibration method, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining a plurality of target poses corresponding to a calibration plate, and determining a target pixel coordinate corresponding to an angular point under each target pose based on the angular points on the calibration plate and the image size of a camera; acquiring a current image of the calibration plate under a current pose acquired by the camera, determining a current pixel coordinate corresponding to an angular point in the current image, adjusting the calibration plate from the current pose to a corresponding target pose based on the current pixel coordinate corresponding to the angular point and the target pixel coordinate, and acquiring a target image corresponding to the calibration plate by using the camera; calibrating the camera by using the target images under the plurality of target poses to obtain a plurality of groups of candidate camera internal parameters; and acquiring a verification image corresponding to the verification plate by using the camera, and obtaining a target camera internal reference from the multiple groups of candidate camera internal references based on a distortion removal effect of each group of candidate camera internal references on the verification image. According to the scheme, the convenience and precision of camera calibration can be improved.

The present invention discloses a chip pin measurement method and device based on an adaptive rectangular frame, wherein the method includes: obtaining an image of the chip to be measured; based on the obtained image of the chip to be measured, determining a first region of interest and solving the minimum bounding rectangle of the first region of interest; calculating the four corner points of the minimum bounding rectangle and sequentially sorting the four corner points, wherein the pins on any side of the first region of interest correspond to two of the sorted four corner points; selecting all target pins on any side of the first region of interest, and drawing an adaptive measurement rectangular frame for the target pins based on the positions of the two corner points corresponding to the target pins and the reference parameter values ​​of the target pins; based on the adaptive measurement rectangular frame, determining a second region of interest and solving the pin edges within the second region of interest; and obtaining data of the target pins based on the pin edges. This method can reduce measurement difficulty, reduce calculation complexity, and improve the reliability and stability of measurement results.

The embodiment of the invention relates to the field of displacement monitoring and data processing, and provides a real-time displacement acquisition method based on machine vision and a related device, and the method comprises the steps: obtaining a first image of a reference point and n target monitoring points at a t moment, and obtaining a first image set; according to the initial parameter information set and the first image set, target center corner sub-pixel-level position information corresponding to the reference point and the n target monitoring points is determined, and target center corner sub-pixel-level position information corresponding to the reference point and a target center corner sub-pixel-level position information set corresponding to the n target monitoring points are obtained; determining a first relative position information set according to the sub-pixel-level position information set of the central angular points of the n target monitoring point targets and the sub-pixel-level position information of the central angular points of the reference point targets; acquiring a second relative position information set of the n target monitoring points at the t-1 moment; according to the first relative position information set and the second relative position information set, the displacement variations corresponding to the n target monitoring points are determined, and the accuracy and accuracy of the displacement variations are improved.

Systems and methods are described relating to pose and shape estimation of objects. In some examples, a camera generates images depicting an object from different viewpoints. Within the images, a system identifies corners of the object, and the system uses these corners to generate lines that are projected from different viewpoints through the corners. Points may be identified by intersecting lines such that the points may be used to generate estimations of the object. The estimation with the highest score may be used to place the object in a location different from where the object was located.

The invention relates to the technical field of mechanical arm control, in particular to a collision detection and pose adjustment method and system for picking in a mechanical arm box. The method comprises the following steps: firstly, projecting a three-dimensional point cloud of a box body to a two-dimensional table-board coordinate system, matching to obtain an initial relative pose, performing iterative registration on the three-dimensional point cloud of the box body and a three-dimensional template point cloud according to an initial relative pose relationship, and obtaining coordinates of inner and outer angular points of the box body; then, the three-dimensional point cloud of the box body is converted into a box body coordinate system according to the coordinates of the inner and outer angular points of the box body, and a space plane equation of each side wall of the box body is obtained; then, judging whether the collision risk of the box body occurs or not by calculating the intersection point distance between the pose ray of the sorting point and the side wall of the box body; if so, generating an execution vector; otherwise, pose point optimization is carried out, sorting task execution information is generated according to the pose point optimization, it is ensured that the mechanical arm does not collide with the side wall when grabbing in the box body, and the operation safety and reliability are improved.

The invention relates to a marker (400), in particular a two-dimensional marker, which is optically detectable and has a polygonal, in particular rectangular, marker base shape (402) with corners (404), wherein the marker has at one or more of the corners (404) a teardrop-shaped extension (406) located outside the marker base shape (402), which creates a saddle point at the respective corner. The invention also relates to an object with such a marker and to a method for determining the position of the saddle points.

The invention relates to an electronic equipment parameter calibration method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: in response to a triggered calibration starting operation, obtaining a corner image containing a target calibration pattern and distance information; performing angular point extraction on the angular point image to obtain image coordinates of each angular point in the angular point image; on the basis of the image coordinates of all the angular points, the internal parameters and distortion parameters of the rearview mirror lens and the world coordinates of all the angular points, the calibration external parameters of the rearview mirror lens are determined; wherein the world coordinate of each angular point is determined based on the distance information; and determining a calibration result of the calibration external parameter based on the precision value of the calibration external parameter. By adopting the method, the parameter calibration accuracy of the electronic equipment can be ensured, and the parameter calibration efficiency of the electronic equipment can be effectively improved.

The invention relates to a camera pose determination method and device, a medium, electronic equipment and a program product, and the method comprises the steps: obtaining an RGB image and a depth image which are shot by a camera and are used for describing an inverse color calibration board, and the inverse color calibration board is obtained through the inversion of the color of the calibration board; according to the target image, the depth image and the camera internal reference, determining a first three-dimensional coordinate of a target feature point in the target image in a camera coordinate system, the target image being an image obtained by performing color inversion processing on the RGB image, and the target feature point being an angular point of a black square block or a central point of the black square block in the target image; performing point cloud matching on the first three-dimensional coordinate and a second three-dimensional coordinate of the target feature point in a calibration plate coordinate system to obtain an initial camera pose; according to the camera internal reference, the second three-dimensional coordinate, the pixel coordinate of the target feature point and the initial camera pose, the target camera pose is determined, and the estimation precision of the target camera pose determined by depending on the initial camera pose is improved.

An error correction method and device for a line structured light 3D camera. The method comprises: placing a 3D calibration plate at different positions in the field of view of the 3D camera, and allowing a relative motion to scan the 3D calibration plate to obtain multiple sets of point cloud data at different positions; processing the point cloud data and calculating corner coordinates of the 3D calibration plate corresponding to each set of point cloud data; constructing an error correction model by using an inclination angle, caused by an error, between a straight line along which the relative motion direction lies and a laser plane of the 3D camera as an error model correction parameter; calculating error correction model parameters according to a space vector constraint relationship between corner points; and applying the model to the point cloud data of a measured object to obtain distortion-free point cloud data.

This information processing device (100) comprises: an acquisition unit (120) that acquires a panoramic image including an object that is a cube or a rectangular parallelepiped; a detection unit (130) that detects the object from the panoramic image; and a determination unit (140) that, when four corners of the object are detected, determines whether a circle passing through four points corresponding to the four corners can be calculated, and when the circle passing through the four points can be calculated, determines that the accuracy of the four corners is high.

The invention provides an instance segmentation method and device in the field of computer vision, which are used for aligning primitives segmented in a three-dimensional model based on a two-dimensional instance in an open scene so as to output three-dimensional instance segmentation with consistency, and the same three-dimensional instance can be segmented even if a visual angle is switched. The method comprises the following steps: acquiring at least one image of a target scene, a camera view angle of the at least one image and a three-dimensional model of the target scene; instance segmentation is carried out on the at least one image to obtain a first two-dimensional instance segmentation result, and the first two-dimensional instance segmentation result comprises at least one two-dimensional instance; obtaining at least one primitive in the three-dimensional model, wherein the at least one primitive comprises primitives formed by angular points and surface patches in the three-dimensional model; then projecting at least one two-dimensional instance and at least one primitive based on a camera visual angle, and determining at least one three-dimensional instance that each three-dimensional instance comprises one or more primitives; and outputting the instance identifier of each three-dimensional instance.

According to the method, continuous geometric parameters are adopted to represent CGR-OBB to replace traditional rotation angle or angular point coordinate parameters, and nine continuous learnable parameters are constructed to represent a rotation target bounding box in any direction, so that the problems of discontinuous angles, fuzzy decoding and the like in existing rotation target detection are solved; and continuous representation and unique decoding of the directional bounding box are realized. Besides, the invention provides a rotating target detection method based on directional bounding box continuous geometric representation, a unified encoding and decoding module is designed and is used for realizing bidirectional conversion between a real OBB and continuous parameters, and the method can be directly integrated into various mainstream rotating target detectors, so that the detection precision is remarkably improved. The method can be widely applied to high-resolution remote sensing image analysis, satellite-borne remote sensing platforms, small target detection and other scenes.

The present invention relates to a three-dimensional coordinate measurement method and system based on spot tracking, comprising selecting an initial image from a pre-acquired image pair with epipolar geometric constraints, extracting the initial spot of a ground feature, and calculating an initial offset value between the initial spot and the centroid of the corresponding tracking spot in the image pair; performing a secondary calibration on the coordinates of the corner points selected in the initial image and their corresponding matching points; and calculating the three-dimensional coordinates of all corner points based on the calibrated point pairs and left and right camera parameters to obtain the three-dimensional coordinates of the ground feature. The present invention extracts the initial spot of the initial image, calculates the initial offset value between the centroid of the corresponding tracking spot in the image pair, performs a secondary calibration on the coordinates of the pre-selected corner points and their matching points in the initial image, and finally calculates the three-dimensional coordinates of all corner points to obtain the three-dimensional coordinates of the ground feature. This method does not require the use of equipment such as 3D glasses, greatly improving the convenience of three-dimensional coordinate measurement of ground features and ensuring measurement accuracy.

The invention provides an unstacking and stacking method, device and equipment, and relates to the field of visual algorithm recognition. The method comprises the following steps: acquiring actual three-dimensional point cloud data of a target material; intercepting target point cloud data in the actual three-dimensional point cloud data according to the attribute information of the target material; converting the target point cloud data into a two-dimensional image; wherein the attribute information is an actual accumulation parameter. According to the two-dimensional image, determining a target angular point of the target material, and determining an angular point position and a rotation angle of the target angular point; and according to the angular point position and the rotating angle, a grabbing posture is determined, and the grabbing posture is sent to a preset mechanical arm controller, so that the mechanical arm controller executes stacking and unstacking operation on the materials according to the grabbing posture. The method is used for achieving the effect of improving the stacking and unstacking positioning precision.

This application provides a five-axis measurement and evaluation method for wheel-type tenon grooves, relating to the field of wheel-type tenon groove measurement technology. After the wheel is clamped, a wheel coordinate system is established. Based on the nominal position and orientation of the tenon groove, a nominal coordinate system for the tenon groove is established, and correction measurement points are collected on the working surface to be measured. The initial coordinate system of the tenon groove is obtained by correcting it according to the least squares criterion. A high-density point cloud is obtained by five-axis oscillation scanning and fitted to the actual working surface. The nominal corner points are projected onto the actual working surface to obtain the measured corner points. The coordinate system is corrected using the least squares method for corner point deviation. The oscillation-fitting-correction process is iterated until the change in coordinate system between two adjacent iterations is less than 10% of the tolerance bandwidth, thus obtaining the measured coordinate system of the tenon groove. Geometric tolerances such as center point position, axial / radial tilt, and angle are calculated in the wheel coordinate system to complete the machining quality evaluation. This method reduces the accumulated error of the reference structure and improves the accessibility and measurement repeatability of oblique tenons.

The pose estimation method comprises the following steps: acquiring a reference image set for performing pose estimation on a target object contained in a target image; wherein the reference images in the reference image set respectively comprise the target object at different visual angles; the view angle of the target object contained in the target image is different from the view angle of the target object contained in the reference image; performing three-dimensional reconstruction on the target object based on the reference image set to obtain a three-dimensional model corresponding to the target object; constructing a three-dimensional bounding box surrounding the target object based on the three-dimensional model, and obtaining position coordinates of angular points of the three-dimensional bounding box; and performing pose estimation calculation on the target object contained in the target image based on the position coordinates of the angular points of the three-dimensional bounding box.

In implementations of techniques and systems for chamfer tools in volumetric sculpting software, a processing device receives an indication of a brushed region of a three-dimensional (3D) object to be chamfered and a chamfer size. A machine-learning model determines surface voxels in the brushed region representing an edge or corner voxel. The machine-learning model also determines parameters for the edge or corner voxel that define a chamfer plane and a chamfer coefficient. The chamfer plane is then moved in a direction normal to the chamfer plane by a distance based on the chamfer size and the chamfer coefficient. To generate a chamfer, the processing device performs an addition or subtraction operation on the 3D object to the moved chamfer plane for the edge or corner voxel.

The present invention discloses a method, system, device and medium for projection single-pose calibration, which relates to the field of computer vision and projection interaction technology. The method includes: generating multiple calibration patterns, projecting them onto a calibration plane, collecting grayscale images, performing corner detection and sub-pixel refinement processing, obtaining the corner point correspondence between the projector image and the camera image, iteratively solving the projection matrix of the projector and the camera, separating the intrinsic parameter matrix and the extrinsic parameter matrix, calculating the basic matrix and the essential matrix, and decomposing the rotation matrix and translation vector of the camera relative to the projector; estimating the camera imaging distortion, obtaining the distortion correction coefficient, and performing distortion correction; statistically calculating the reprojection error generated during the correction process, and adjusting the parameters of the projector and camera until the error meets the preset accuracy requirements. Projector parameter calculation is completed by projection single-pose calibration, and the calibration process does not require posture adjustment, thereby improving the degree of automation and reducing manual intervention.

The invention provides a corner position identification-based processing starting point determination method, device and chip, and the method comprises the following steps: determining a corner position identification corresponding to each corner point of a target primitive according to the relative position relation between each corner point of the target primitive and all rectangular edges of a target processing frame; the angular point position identifiers comprise flag bits in one-to-one correspondence with the rectangular edges; and sequentially processing each triangular edge according to the processing sequence, and if the angular point position identifiers of the two end points of the current triangular edge have the condition that the value of the flag bit corresponding to the same rectangular edge is a second preset value, ignoring the current triangular edge. The number of times of calculating whether the triangular edge and the rectangular edge have the intersection point can be reduced, so that the calculation power consumption is reduced.