Accurate integration of multi-view range images using k-means clustering
Pattern Recognition
Constrained curve fitting on manifolds
Computer-Aided Design
A clustering approach to free form surface reconstruction from multi-view range images
Image and Vision Computing
From unordered point cloud to weighted B-spline: a novel PCA-based method
AMERICAN-MATH'11/CEA'11 Proceedings of the 2011 American conference on applied mathematics and the 5th WSEAS international conference on Computer engineering and applications
Haptic data compression based on quadratic curve reconstruction and prediction
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
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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 Bspline 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.