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ABSTRACT
Given a large set of irregularly spaced points in the plane, an algorithm for partitioning the points into subsets and fitting a parametric curve to each subset is described. The points could be measurements from a physical phenomenon, and the objective in this process could be to find patterns among the points and describe the phenomenon analytically. The points could be measurements from a geometric model, and the objective could be to reconstruct the model by a combination of parametric curves. The algorithm proposed here can be used in various applications, especially where given points are dense and noisy. Examples demonstrating the behavior of the algorithm under noise and density of the points are presented and discussed.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 6
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Siu-Wing Cheng , Stefan Funke , Mordecai Golin , Piyush Kumar , Sheung-Hung Poon , Edgar Ramos, Curve reconstruction from noisy samples, Computational Geometry: Theory and Applications, v.31 n.1-2, p.63-100, May 2005
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Manfred Weiler , Ralf Botchen , Simon Stegmaier , Thomas Ertl , Jingshu Huang , Yun Jang , David S. Ebert , Kelly P. Gaither, Hardware-Assisted Feature Analysis and Visualization of Procedurally Encoded Multifield Volumetric Data, IEEE Computer Graphics and Applications, v.25 n.5, p.72-81, September 2005
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REVIEW
"Nickolas S. Sapidis : Reviewer"
A huge number of techniques are available for fitting
a single curve to a set of points. The author of this paper
correctly identifies two related problems that have received much
less attention by the research community. First problem: ident
more...
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