NDLI: Reconstructing B-spline Curves from Point Clouds--A Tangential Flow Approach Using Least Squares Minimization

Content Provider	IEEE Xplore Digital Library
Author	Yang Liu Huaiping Yang Wenping Wang
Copyright Year	2005
Description	Author affiliation: Dept. of Comput. Sci., Hong Kong Univ. (Yang Liu; Huaiping Yang; Wenping Wang)
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
Starting Page	4
Ending Page	12
File Size	239033
Page Count	9
File Format	PDF
ISBN	076952379X
DOI	10.1109/SMI.2005.39
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-06-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Spline Least squares methods Curve fitting Clouds Image reconstruction Least squares approximation Minimization methods Multilevel systems Geometry Clustering algorithms
Content Type	Text
Resource Type	Article

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