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- W2129121943 abstract "We present a novel algorithm based on least-squares minimization to approximate point cloud data in 2D plane with a smooth B-spline curve. The point cloud data may represent an open curve with self intersection and sharp corner. Unlike other existing methods, such as the moving least-squares method and the principle curve method, our algorithm does not need a thinning process. The idea of our algorithm is intuitive and simple - we make a B-spline curve grow along the tangential directions at its two end-points following local geometry of point clouds. Our algorithm generates appropriate control points of the fitting B-spline curve in the least squares sense. Although presented for the 2D case, our method can be extended in a straightforward manner to fitting data points by a B-spline curve in higher dimensions" @default.
- W2129121943 created "2016-06-24" @default.
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- W2129121943 date "2006-01-05" @default.
- W2129121943 modified "2023-10-16" @default.
- W2129121943 title "Reconstructing B-spline Curves from Point Clouds--A Tangential Flow Approach Using Least Squares Minimization" @default.
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- W2129121943 doi "https://doi.org/10.1109/smi.2005.39" @default.
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