Abstract
In this paper, we combine Kazhdan’s FFT-based approach to surface reconstruction from oriented points with adaptive subdivision and partition of unity blending techniques. The advantages of our surface reconstruction method include a more robust surface restoration in regions where the surface bends close to itself and a lower memory consumption. The latter allows us to achieve a higher reconstruction accuracy than the original global approach. Furthermore, our reconstruction process is guided by a global error control achieved by computing the Hausdorff distance of selected input samples to intermediate reconstructions.
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Schall, O., Belyaev, A., Seidel, HP. (2006). Adaptive Fourier-Based Surface Reconstruction. In: Kim, MS., Shimada, K. (eds) Geometric Modeling and Processing - GMP 2006. GMP 2006. Lecture Notes in Computer Science, vol 4077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11802914_3
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DOI: https://doi.org/10.1007/11802914_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36711-6
Online ISBN: 978-3-540-36865-6
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