12 results about "Corner point detection" patented technology

The application relates to the technical field of image splicing, and discloses a video transmission high-definition image intelligent splicing method and system; the system comprises an image preprocessing module, a feature point matching and screening module, an image optimal splicing seam generation module and a video output module; first, a video is acquired and dynamic range equalization is carried out, an adaptive noise reduction method is used for filter processing, and image correction is implemented; second, an adaptive corner point detection algorithm is used for feature point extraction, feature points are matched based on multidimensional space data indexing, a feature point matching pair is obtained, and feature point screening is carried out; then, an overlapping area is searched, a dynamic search algorithm is introduced to generate an image optimal splicing path, and an image optimal splicing seam is obtained; finally, the image is divided according to a dynamic grid, and video output is realized by using priority sorting; the application realizes the purpose of image intelligent splicing by processing and splicing the video image, and the method is accurate and objective.

This invention discloses an eye-tracking method and system based on multimodal corner-eye detection. The method includes: Step 1, acquiring user eye image data in real time and performing image enhancement processing; Step 2, multimodal corner-eye detection, sequentially performing initial detection and verification, refined detection, and iterative optimization detection, to obtain candidate corner-eye points through initial detection and verification, accurately locate the corner-eye point position through refined detection, and iteratively optimize the detection results of each frame through iterative optimization detection; Step 3, dynamic slip detection, including: continuously monitoring the positional changes of the corner-eye points of both eyes relative to the corner-eye points of a reference frame, using a single-threshold dual-level judgment mechanism to determine whether device slip has occurred; and updating the corner-eye point data of the reference frame when device slip occurs, and automatically triggering a recalibration process to update the position of the corner-eye points of the reference frame. This invention solves the problem that existing solutions have shortcomings in device slip detection, which leads to a significant decrease in tracking accuracy.

The application relates to a camera external parameter calibration method of a vehicle-mounted panoramic all-around viewing system, which comprises the following steps: S1, arranging a calibration site according to the size of a vehicle, and preparing four ground markers and a ruler; S2, placing a vehicle to be calibrated in a calibration area; S3, randomly placing the ground markers in the ROI of the common viewing area, and measuring the world coordinates of one of the ground markers; S4, detecting the position of the corner point of the ground marker in the ROI area of the fisheye image according to a corner point detection algorithm, and removing distortion; S5, numbering the detected corner points; S6, calibrating the initial external parameters of all the cameras, and calculating the 3d world coordinates of the corner points; S7, constructing a least square equation according to the 3d world coordinates, the corner point coordinates and the projection relationship therebetween, performing closed loop BA optimization, and obtaining the final more accurate external parameters. Therefore, the after-sales calibration precision can be improved by randomly laying the ground markers in the ROI of the common viewing area of the two adjacent cameras.

Embodiments of the present application provide a feature point extraction method and device for an image, electronic equipment and a storage medium, wherein the method comprises: obtaining an original image; performing semantic segmentation on the original image to obtain a segmented semantic image; performing grid division on the segmented semantic image to obtain a grid image; performing high threshold corner point detection on the grid image to obtain first feature point information; and performing secondary corner point detection on the grid image according to the first feature point information to obtain feature points. By implementing the embodiments of the present application, the extraction efficiency of feature points can be improved, the extraction accuracy of feature points can be improved, and high-precision feature point extraction can also be achieved for regions with no obvious changes in image pixels.

The application discloses a method for extracting roof geometry and semantic features, an electronic device and a storage medium, and relates to the technical field of computing; the method comprises the following steps: S1, roof point cloud surface fitting; S2, accelerating initial extraction of the boundary by using alpha-shape and Delaunay triangular net, wherein the alpha value is reversely and adaptively adjusted according to the local point cloud density in the alpha-shape algorithm; S3, Gaussian smoothing denoising; S4, adaptive corner point detection; S5, boundary line segment fitting, bidirectional geometry verification and accurate extraction. The core logic is initial extraction-optimization-accurate extraction, the acceleration calculation and geometry verification mechanism are integrated, the combination of reversely and adaptively adjusting the alpha value and the Delaunay triangular net reduces the calculation redundancy, improves the working efficiency of obtaining the building top feature corner points from the roof point cloud data, and can output higher-precision contour lines and roof feature corner points.

The embodiment of the application provides a table recognition reconstruction method and device, a storage medium and an interactive tablet. The method comprises the following steps: when a trigger operation of a circle selection button on a stylus is listened to, obtaining target content obtained by the stylus through circle selection on a touch screen; when the target content comprises a table image, performing corner point detection on the table image to obtain each corner point of the table image and the position coordinates of the corner points; obtaining the position coordinates of each cell of the table image according to the position coordinates of the corner points; in the table image, cutting and obtaining the image of each cell; obtaining the text content in each cell; reconstructing the table structure of the table image according to the position coordinates of each cell; filling the text content in each cell into the corresponding cell in the reconstructed table structure to obtain a reconstructed table. The embodiment of the application saves the development cost, has small running amount, occupies less memory, has simple design, and improves the table reconstruction efficiency.

A cable vibration frequency identification method based on visual cooperative segmentation, comprising the following steps: S1, key frame extraction is performed on a cable vibration video to obtain a key frame image; S2, the key frame image is input into a target detection model to perform coarse-grained target detection and obtain target detection information; S3, the target detection information is input into an image segmentation model to perform mask segmentation on the key frame image, obtain a mask image, and obtain a mask region; S4, a corner point detection algorithm is used in the mask region to extract feature points; S5, the corner points are tracked between frames based on an optical flow method to obtain a displacement sequence of the corner points; and S6, frequency domain analysis is performed on the displacement sequence to extract a vibration frequency. The application also relates to a computer storage medium storing a program for executing the above method. The application does not need a physical target, does not need manual ROI initialization, and can realize multi-target cable vibration frequency in a complex environment, and belongs to the field of structural health monitoring.

The application provides a multi-source fusion positioning and pose determination method and system based on lane line structure assistance, comprising: fusing satellite pseudo-range observation values, phase observation values, acceleration values, gyroscope observation information and visual images for positioning processing; obtaining positions, velocities and attitudes at an initial time, performing initial alignment and mechanical arrangement through inertial navigation to obtain positions, velocities and attitudes at subsequent times; extracting lane lines in the visual images by using a preset lane line extraction algorithm; extracting and matching line features in the visual images by using a real-time straight line segment detection algorithm and a line band descriptor algorithm, and extracting and matching corner point features in the images by using a corner point detection algorithm and an optical flow method; obtaining a current world main direction based on the lane lines and the gravity direction, and initializing structure line features of the current world; and using the main direction to constrain the direction of the line features, continuously optimizing the positions, velocities and attitudes at the subsequent times through the corner point features and the constrained line features.

The invention provides a camera external parameter calibration method and system, computer equipment and a medium, and the method comprises the steps: obtaining a target image, obtaining an image containing a preset region from the target image, and taking the image as a region-of-interest image; performing corner detection on the region-of-interest image to obtain pixel coordinates of corners in the preset region in the region-of-interest image; based on the pixel coordinates of the angular points in the preset region in the region-of-interest image and the pixel coordinates of the region-of-interest image in the target image, determining the pixel coordinates of the angular points in the preset region in the target image; and performing external parameter calibration on the target camera according to the pixel coordinates of the angular points in the preset area in the target image. When the target camera after external parameter calibration is used for generating the panoramic image picture, the problem that the panoramic image picture cannot be generated or the effect of the generated panoramic image picture is poor due to the fact that the brightness difference exists when the target camera carries out image shooting caused by the external environment can be relieved or solved.

The application discloses a high-robustness and high-precision camera calibration board and an angle point detection method. The method comprises the following steps: forming an expected calibration board by combining an ArUco code pattern and a black-and-white checkerboard pattern; establishing a calibration board coordinate system and setting an ArUco code pattern angle point in the calibration board coordinate; collecting a calibration board image to obtain a pixel coordinate of the ArUco code pattern angle point; using the calibration board coordinate and the pixel coordinate to solve a projection transformation matrix T from the calibration board coordinate system to a pixel coordinate system; using the projection transformation matrix T and a known model of the calibration board to calculate a pixel coordinate of a black-and-white checkerboard angle point; and using a sub-pixel algorithm to obtain an accurate pixel coordinate of the black-and-white checkerboard angle point. The application solves the problems of low accuracy of the ArUco code pattern angle point coordinate, a small number of angle points, and the black-and-white checkerboard pattern being easily affected by environmental interference, a placing posture, backlight, local shadow and the like, leading to detection failure and angle point loss.

The application discloses a kind of based on principal component analysis's firebrick three-dimensional measurement method, method includes: obtaining the point cloud data of the firebrick to be measured;Point cloud data is filtered and screened, and the upper surface point cloud after processing is obtained;PCA is used to the upper surface point cloud, and data dimension reduction processing is carried out, and three-dimensional point cloud is converted into two-dimensional point cloud;According to two-dimensional point cloud, the length and width of firebrick are calculated;Two-dimensional point cloud is perspective projection and is converted into gray image, and corner point detection is carried out in gray image, and the number of corner points is obtained;According to the number of corner points, the projection relationship of image corner point and two-dimensional point cloud and the corresponding relationship of two-dimensional point cloud and three-dimensional point cloud in principal component analysis method, the three-dimensional vertex of firebrick corresponding to image corner point is found, and the thickness of firebrick is calculated according to the distance from three-dimensional vertex to reference plane;The length, width and thickness of firebrick are output.The method can accurately and quickly detect the three-dimensional parameters of firebrick.

Embodiments of the present disclosure disclose a parking space reconstruction method and device, electronic equipment and a storage medium, wherein the method comprises: determining, based on first parking space corner point detection results respectively corresponding to each frame in a current frame set, a first number of second parking space corner point detection results that meet a preset condition in terms of observation confidence of each detected parking space; determining a first state quantity respectively corresponding to each parking space in the current frame set; optimizing each first state quantity based on each second parking space corner point detection result respectively corresponding to each parking space in the current frame set and a preset optimization rule, to obtain an optimized second state quantity respectively corresponding to each parking space in the current frame set; and determining a target position in a first coordinate system respectively corresponding to each parking space based on the second state quantity respectively corresponding to each parking space. The embodiments of the present disclosure can effectively improve the robustness of parking space optimization, thereby improving the accuracy of the obtained parking space position.