7 results about "Corner detector" patented technology

The invention discloses a state estimation method based on mixed features and adaptive key frame selection, and belongs to the field of autonomous navigation of unmanned systems. The implementation method comprises the following steps of: acquiring a plurality of images, and synchronously acquiring inertial measurement data of a six-axis IMU (Inertial Measurement Unit); the method comprises the following steps: performing key frame decision on a current frame image according to inertial measurement data, and classifying the image into a key frame image and a non-key frame image: acquiring a key frame feature matching set through an entropy maximization self-supervision feature extractor and an image attention matcher, and constructing a visual reprojection error term based on triangulation map points; non-key frame feature points are extracted by adopting an improved corner detector, feature displacement is obtained through IMU constraint optical flow tracking, and a visual re-projection error and an IMU pre-integration residual term are generated; and based on a vision-inertia tight coupling optimization module solution system, combining a vision reprojection error, an IMU pre-integration residual error and a pneumatic constraint residual error to construct a tight coupling optimization problem, and solving an optimal pose state. The method is beneficial to navigation of the small-sized high-speed unmanned aerial vehicle.

Embodiments of the present application relate to the field of optical tomography technology, and in particular to a computer vision-driven optical tomography reconstruction method and system. The method includes the following steps: obtaining microscopic projection images of cells in multiple directions; identifying the cells in the microscopic projection images and cropping the microscopic projection images into images with consistent sizes; separating the cells from the background area; determining the exact positions of the cells in each frame based on the high contrast of the images after cell segmentation and precisely aligning the positions of the segmented cells; using a Harris corner detector to implement dynamic feature extraction on the cell rotation video; using an optical flow method to track the feature motion in the image sequence and calculating the rotation angle of the cells; generating a sinogram based on the microscopic projection images and the rotation angles of the corresponding cells, and reconstructing the three-dimensional intensity distribution of the cells. The present application utilizes computer vision technology to improve the speed, robustness, and accuracy of optical tomography image reconstruction.

This application relates to the fields of computer vision and autonomous driving perception technology, and particularly to a method, apparatus, device, medium, and program product for generating panoramic parking space data. The method includes: acquiring an original AVM image and preprocessing it to obtain a clean background image; generating parameterized parking spaces based on a preset set of candidate parking space contour primitives and preset multi-dimensional parameters, and mapping the parameterized parking spaces to the clean background image based on the coordinate system of the original AVM image to obtain an initial parking space image set; calculating the corner detection loss of each parking space image in the initial parking space image set based on a preset parking space corner detector, and generating a final parking space image set based on the corner detection loss of each parking space image from the initial parking space image set. This solves the problems of difficulty in simultaneously achieving background realism and foreground controllability, and low efficiency of data selection mechanisms in related technologies, thus improving the realism of the synthesized data.

A method for adaptive corner detection is provided. The method includes: obtaining one or more event data from a dynamic vision sensor; capturing and organizing a plurality of recorded events of the event data into a 2D array; transforming the 2D array into one or a plurality of Ordered Surface (OS) matrices by populating one or a plurality of empty Image Matrices with the recorded events based on their coordinates and assigning order values; and applying a corner detector to the OS matrices. A system for adaptive corner detection is also provided.

This invention provides an image feature extraction method, relating to the field of image processing technology. The image feature extraction method includes the following steps: performing texture analysis on the image to be extracted, and determining the grid size and / or the number N of feature points to be extracted within the grid based on the results of the texture analysis. cell When the grid size is determined based on the texture analysis results, the image to be extracted is divided into grid regions according to the grid size; when the number N of feature points to be extracted within the grid is determined based on the texture analysis results... cell At that time, a corner detector is used to extract feature points within the grid. The number of extracted feature points is denoted as N. It is then determined whether N is greater than N0. cell When N>N cell When N ≤ N, the extracted feature points are filtered, and the filtered feature points are used as the feature points of the grid output; cell In this process, the extracted feature points are directly used as the feature points output by the grid. This invention fully considers the distribution of texture in the image, making the extracted feature points more reflective of the image's characteristics.

A coal mine tunnel roof multipoint horizontal and vertical displacement measuring device comprises at least two groups of measuring assemblies and positioning assemblies, a front rod of the lower group of measuring assemblies is hinged to a corner detector of a rear rod of the upper group of measuring assemblies, the front rod of each group of measuring assemblies is provided with the positioning assembly, and the positioning assemblies are arranged on the front rod of the lower group of measuring assemblies. The measuring assemblies are fixed in the hole channel through the supporting plates, the hole channel surrounding rock change condition is transmitted to the measuring assemblies in real time, the expansibility of the device is improved through the mutual splicing mode of the measuring assemblies, and meanwhile the measuring devices of the measuring assemblies are matched with one another; through the axial displacement, the axial swing amount and the radial rotation amount, the change condition of the hole surrounding rock is truly reflected, the detection precision is improved, and the on-site safety is improved.

A method for adaptive corner detection is provided. The method includes: obtaining one or more event data from a dynamic vision sensor; capturing a plurality of recorded events of the event data and organizing them into a 2D array; transforming the 2D array into one or more ordered surface (OS) matrices by populating one or more empty image matrices with the recorded events based on coordinates of the recorded events and assigning order values; and applying a corner detector to the OS matrix. A system for adaptive corner detection is also provided.