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Free form surface reconstruction method based on LS-SVM

机译:基于LS-SVM的自由形式表面重建方法

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A free form surface reconstruction method based on least square support vector regression is presented. Firstly in order to eliminate noise points, some sample points are chosen from the measured data to construct LS-SVM model. Thus a LS-SVM model to approximate the measured points is obtained. And the distribution probability of the approximation error is figured out. In result, the noise points are eliminated when their error probability is less than the specified threshold value. Then the boundary points are extracted. Lastly the surface model is reconstructed by use of the measured points from which noise points have been eliminated. The results indicate that the reconstruction precision can satisfy the demands of engineering application.
机译:提出了一种基于最小二乘支持向量回归的自由形式的表面重建方法。首先为了消除噪声点,从测量数据中选择一些采样点以构建LS-SVM模型。因此,获得了近似测量点的LS-SVM模型。近似误差的分布概率被弄清楚。结果,当它们的误差概率小于指定的阈值时,消除了噪声点。然后提取边界点。最后,通过使用已经消除了噪声点的测量点来重建表面模型。结果表明,重建精度可以满足工程应用的需求。

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