8results about How to "Improve registration speed" patented technology

The invention belongs to the technical field of ecological monitoring, and discloses a forest ULS-TLS point cloud automatic registration method based on ground context description, and the method employs a ground point as a registration element, constructs a ground context, can directly achieve the registration of TLS single scanning data to a ULS point cloud, and does not need the pre-registration of different scanning point clouds of a TLS. The extraction process of the ground points is relatively standardized, stable and reliable results can be obtained generally, and the method is not affected by distribution, density and shape complexity of trees in the forest. Compared with extraction of tree attributes, the ground points are used as registration primitives, so that the calculation cost is reduced, and high calculation overhead caused by extraction of the tree attributes is avoided. The invention aims to provide a forest ULS-TLS point cloud automatic registration method based on ground context description so as to quickly, accurately and automatically realize registration of forest ULS and TLS point clouds, comprehensively obtain forest structure information and promote application of a laser radar technology in forest investigation.

The invention discloses a transformer substation three-dimensional modeling method based on a self-calibration technology, and relates to the technical field of transformer substation three-dimensional modeling, and the transformer substation three-dimensional modeling method based on the self-calibration technology comprises the following steps: S1, determining the spatial position of point cloud data; s2, coarse registration: performing coarse registration on the point cloud of the power transformation equipment without the specific mark and the point cloud of the power transformation equipment with the specific mark according to the relative position relation of the equipment; s3, data cleaning: performing cleaning and denoising processing on the point cloud to ensure data quality; s4, precise registration: fitting point cloud line and surface information for the point cloud of the power transformation equipment without the specific mark, and carrying out precise registration; according to the transformer substation three-dimensional modeling method based on the self-calibration technology, the calculation complexity can be effectively managed, efficient descriptors are used in the coarse registration stage to reduce the data volume, and therefore the overall registration speed is increased, and robustness can be improved.

This invention relates to the field of computer vision technology, specifically to a point cloud registration method, system, storage medium, and apparatus based on a diffusion model. The method includes: acquiring training samples, including source point clouds and target point clouds; using a point cloud feature extraction module to extract features from the source and target point clouds respectively, obtaining features 1 and 2; using a feature interaction module to fuse features 1 and 2, obtaining features F1 and F2; using a point cloud generation module to generate two aligned point clouds, Ag and Bg; using a transformation matrix prediction module to calculate the correspondence between the original point cloud and the generated point cloud Ag, and between the original point cloud and the generated point cloud Bg, obtaining the predicted transformation matrix and translation vector; calculating the model's loss function, adjusting the model parameters, and completing model training when the loss function converges. This invention, based on a diffusion model, transforms the registration problem into a generation problem, improving the accuracy of point cloud registration.

This application relates to an image detection method, a vertex registration method, and a storage medium. The image detection method includes: acquiring a vertex detection model of a target object; using the vertex detection model to perform local feature detection processing on the image to be detected of the target object, obtaining several vertices on the target object; and outputting several vertices on the target object, each vertex having one or more of the following information: position coordinates, category, bounding rectangle, and enclosing rectangle. In this technical solution, when acquiring the vertex detection model, pre-registration processing is performed on each vertex of the sample images participating in network training, which helps to enhance the image detection performance of the model.

The present application discloses a point cloud registration method, device, electronic device and storage medium, which relate to the field of image processing. The method comprises: randomly determining a focus point; taking the point closest to the focus point in the target point cloud data as a key point; determining a target area in the target point cloud data based on the key point, wherein the key point is located in the target area; registering the target point cloud data and the source point cloud data according to the target area, wherein the source point cloud data and the target point cloud data are located in different point cloud images. The present application solves the technical problems of low computational efficiency and insufficient robustness caused by redundancy and noise in point cloud data.

The application discloses a point cloud data registration method and system, electronic equipment and a storage medium, and the method comprises the following steps: acquiring a model point cloud of a three-dimensional model of a scene and a scene point cloud; performing plane feature extraction on the model point cloud and the scene point cloud to obtain a model point cloud plane feature set and a scene point cloud plane feature set respectively; performing line feature extraction on the model point cloud and the scene point cloud according to the two feature sets to obtain a corresponding model point cloud line feature set and a scene point cloud line feature set; performing feature matching on the model point cloud and the scene point cloud based on the model point cloud plane feature set, the scene point cloud plane feature set, the model point cloud line feature set and the scene point cloud line feature set to determine a feature matching relationship; and determining a coordinate transformation relationship of the model point cloud and the scene point cloud based on the feature matching relationship to register the model point cloud and the scene point cloud. Through the above method, the registration between the three-dimensional model and the point cloud can be realized through the plane feature and the line feature, and the registration efficiency is improved.

The invention discloses a visible light image-thermal infrared image matching method and system for rice phenotypes. The method comprises the following steps: acquiring a plurality of visible light images and thermal infrared images of rice; determining fuzzy areas and non-mask areas of the visible light image and the thermal infrared image; extracting feature points and descriptors of a non-mask area, obtaining matched feature point pairs on the visible light image and the thermal infrared image, and connecting the matched feature point pairs to obtain a connecting line; screening out connecting lines which simultaneously meet the length and angle threshold intervals of the connecting lines; according to fitting points of the feature points of the visible light image and the thermal infrared image mapped to the visible light image after passing through a homography matrix, generating a residual error to screen the feature points of the visible light image close to a correct position; and finally, connecting the feature points on the visible light image with the corresponding feature points on the thermal infrared image to obtain a connecting line which is a final matching result. According to the invention, the problem of mismatching caused by blurring of a part of thermal infrared images due to insufficient illumination can be avoided.

The invention relates to a point cloud registration method and device for an automobile steering knuckle, and the method comprises the steps: obtaining a source point cloud set and a target point cloud set corresponding to the steering knuckle; dividing the point clouds in the source point cloud set into a voxel grid, and performing downsampling on the point clouds in the source point cloud set based on the distance between the points in the voxel grid and the centroid in the voxel grid; feature point detection is carried out on the source point cloud set and the target point cloud after downsampling, and registration is carried out on the source point cloud set and the target point cloud after downsampling based on feature points; and determining a plurality of point cloud pairs from the downsampled source point cloud set and the target point cloud, setting different weights for the point cloud pairs with different Euclidean distances, and obtaining a registered point cloud set based on a preset error function. Through the method and the device, the problem of relatively low registration efficiency of a registration task for the point cloud of the complex mechanical part in the prior art is solved.