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Moving least squares is a method of reconstructing continuous functions from a set of unorganized point samples via the calculation of a weighted least squares measure biased towards the region around the point at which the reconstructed value is requested. In computer graphics, the moving least squares method is useful for reconstructing a surface from a set of points. Often it is used to create a 3D surface from a point cloud through either downsampling or upsampling. ==Definition== Consider a function and a set of sample points where and the 's are real numbers. Then, the moving least square approximation of degree at the point is where minimizes the weighted least-square error : over all polynomials of degree in . is the weight and it tends to zero as . In the example . The smooth interpolator of "order 3" is a quadratic interpolator. 抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「moving least squares」の詳細全文を読む スポンサード リンク
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