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Stable Spectral Mesh Filtering

机译:稳定的光谱网格滤波

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摘要

The rapid development of 3D acquisition technology has brought with itself the need to perform standard signal processing operations such as filters on 3D data. It has been shown that the eigenfunctions of the Laplace-Beltrami operator (manifold harmonics) of a surface play the role of the Fourier basis in the Euclidean space; it is thus possible to formulate signal analysis and synthesis in the manifold harmonics basis. In particular, geometry filtering can be carried out in the manifold harmonics domain by decomposing the embedding coordinates of the shape in this basis. However, since the basis functions depend on the shape itself, such filtering is valid only for weak (near all-pass) filters, and produces severe artifacts otherwise. In this paper, we analyze this problem and propose the fractional filtering approach, wherein we apply itera-tively weak fractional powers of the filter, followed by the update of the basis functions. Experimental results show that such a process produces more plausible and meaningful results.
机译:3D采集技术的飞速发展带来了对标准信号处理操作(例如对3D数据进行过滤)的需求。研究表明,表面的Laplace-Beltrami算符的本征函数(流形谐波)在欧几里得空间中起傅立叶基础的作用;因此,可以在歧管谐波的基础上进行信号分析和合成。特别地,通过在此基础上分解形状的嵌入坐标,可以在歧管谐波域中进行几何形状滤波。但是,由于基函数取决于形状本身,因此这种滤波仅对弱(近通)滤波器有效,否则会产生严重的伪影。在本文中,我们分析了这个问题并提出了分数滤波方法,其中我们应用了迭代的滤波器的弱分数幂,然后更新了基函数。实验结果表明,这样的过程产生了更合理和有意义的结果。

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