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Automatic extraction of complex surface models from range images using a trimmed-rational Bezier surface

机译:使用修整有理的Bezier曲面从距离图像中自动提取复杂的曲面模型

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Abstract: This paper presents a new method for the extraction of a rational Bezier surface from a set of data points. The algorithm is divided into four parts. First, a least median square fitting algorithm is used to extract a Bezier surface from the data set. Second, from this initial surface model an analysis of the data set is performed to eliminate outliers. Third, the algorithm then improves the fit over the residual points by modifying the weights of a rational Bezier surface using a non-linear optimization method. A further improvement of the fit is achieved using a new intrinsic parameterization technique. Fourth, an approximation of the region boundary is performed using a NURB with knots. Experimental results show that the current algorithm is robust and can precisely approximate complex surfaces. !19
机译:摘要:本文提出了一种从一组数据点中提取有理贝塞尔曲面的新方法。该算法分为四个部分。首先,使用最小中值平方拟合算法从数据集中提取Bezier曲面。其次,从该初始表面模型进行数据集分析以消除异常值。第三,该算法然后通过使用非线性优化方法修改有理Bezier曲面的权重来改善残差拟合。使用新的固有参数化技术可进一步提高拟合度。第四,使用带结的NURB对区域边界进行逼近。实验结果表明,当前算法是鲁棒的,可以精确地逼近复杂曲面。 !19

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