Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

02/2016

Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

Friday 1st January 2016

Crivellaro, A.; Perotto, S.; Zonca, S.

We propose two algorithms to overcome separately two of the most constraining limitations of surface reconstruction methods in use. In particular, we focus on the large amount of data characterizing standard acquisitions by scanner and the noise intrinsically introduced by measurements. The first algorithm represents an adaptive variant of the multi-level interpolating approach proposed in [Ohtake et al., ACM Transactions on Graphics, 2003], based on an implicit surface representation via radial basis functions. The second procedure is based on a least-squares approximation to filter noisy data. An extensive numerical validation is performed to check the performances of the proposed techniques.