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Asymptotic analysis of discrete normals and curvatures of polylines

机译:折线的离散法线和曲率的渐近分析

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Accurate estimations of geometric properties of a smooth curve from its discrete approximation are important for many computer graphics and computer vision applications. To assess and improve the quality of such an approximation, we assume that the curve is known in general form. Then we can represent the curve by a Taylor series expansion and compare its geometric properties with the corresponding discrete approximations. In turn we can either prove convergence of these approximations towards the true properties as the edge lengths tend to zero, or we can get hints on how to eliminate the error. In this paper, we propose and study discrete schemes for estimating tangent and normal vectors as well as for estimating curvature and torsion of a smooth 3D curve approximated by a polyline. Thereby we make some interesting findings about connections between (smooth) classical curves and certain estimation schemes for polylines.
机译:从平滑曲线的离散近似值准确估计其几何特性对于许多计算机图形学和计算机视觉应用非常重要。为了评估和改善这种近似的质量,我们假设曲线以一般形式已知。然后,我们可以通过泰勒级数展开来表示曲线,并将其几何特性与相应的离散近似值进行比较。反过来,我们可以证明当边缘长度趋于零时,这些近似值趋向于真实属性的收敛性,或者可以得到有关如何消除误差的提示。在本文中,我们提出并研究了离散方案,这些方案用于估计切线和法向矢量,以及用于估计由折线近似的平滑3D曲线的曲率和扭转。因此,我们对(平滑的)经典曲线与某些折线的估计方案之间的连接提出了一些有趣的发现。

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