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• W2105800794 abstract "We develop an adaptive RBF fitting procedure for a high quality approximation of a set of points scattered over a piecewise smooth surface. We use compactly supported RBFs whose centers are randomly chosen from the points. The randomness is controlled by the point density and surface geometry. For each RBF, its support size is chosen adoptively according to surface geometry at a vicinity of the RBF center. All these lead to a noise-robust high quality approximation of the set. We also adapt our basic technique for shape reconstruction from registered range scans by taking into account measurement confidences. Finally, an interesting link between our RBF fitting procedure and partition of unity approximations is established and discussed." @default.
• W2105800794 created "2016-06-24" @default.
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• W2105800794 date "2004-11-13" @default.
• W2105800794 modified "2023-09-23" @default.
• W2105800794 title "3D scattered data approximation with adaptive compactly supported radial basis functions" @default.
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• W2105800794 doi "https://doi.org/10.1109/smi.2004.1314491" @default.
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