3 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.

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.

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.