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Randomized Hough transform (RHT): basic mechanisms, algorithms, and computational complexities
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Convex hulls, occluding contours, aspect graphs and the Hough transform
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International Journal of Computer Vision
Climate Modeling with Spherical Geodesic Grids
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Point-to-line mappings as Hough transforms
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A novel Hough transform algorithm for multi-objective detection
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International Journal of Computer Vision
Journal of Visual Communication and Image Representation
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We propose a randomized-Hough-transform-based method for the detection of great circles on a sphere. We first define transformations from images acquired by central cameras to images on the unit sphere, that is, spherical images. Using the transformations, it is possible to normalize all central-camera images to the spherical image. Therefore, spherical image analysis is a fundamental study for image analysis of central cameras. For geometrical analysis and reconstruction of a three-dimensional space from spherical images, great circles on a sphere are an essential feature since a great circle on a sphere corresponds to a line on a plane in a space. For great-circle detection, we formulate the randomized Hough transform on the basis of the geometric duality of a point and a great circle on a sphere. Finally, as an extension of the randomized Hough transform on a sphere, we propose a method for great-circle detection using a continuous spherical Hough space.