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Non-Delaunay-Based Curve Reconstruction
2002A new non-Delaunay-based approach is presented to reconstruct a curve, lying in 2- or 3-space, from a sampling of points. The underlying theory is based on bounding curvature to determine monotone pieces of the curve. Theoretical guarantees are established.
Sumanta Guha +3 more
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Boundary fitting for 2D curve reconstruction
The Visual Computer, 2009In this paper we present a 3-step algorithm for reconstructing curves from unorganized points: data clustering to filter out the noise, data confining to get the boundary, and region thinning to find the skeleton curve. The method is effective in removing far-from-the-shape noise and in handling a shape of changing density. The algorithm takes O(nlog n)
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Cone Beam Reconstruction with Sources on a Curve
SIAM Journal on Applied Mathematics, 1985From author's summary: ''An inversion procedure is developed for reconstructing a function of compact support in \(R^ 3\) from its divergent beam X-ray transform with source on a curve. Estimates in Sobolev norms are established for the inversion operator.''
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Curve and Surface Reconstruction
2006Many applications in science and engineering require a digital model of a real physical object. Advanced scanning technology has made it possible to scan such objects and generate point samples on their boundaries. This book, first published in 2007, shows how to compute a digital model from this point sample.
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A Method of Curve Reconstruction Based on Point Cloud Clustering and PCA
Symmetry, 2022Kaijun Peng, Jieqing Tan
exaly
Off-the-Grid Curve Reconstruction through Divergence Regularization: An Extreme Point Result
SIAM Journal on Imaging Sciences, 2023Bastien Laville, Gilles Aubert
exaly