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A Curvature-Adaptive Implicit Surface Reconstruction for Irregularly Spaced Points
Sept. 2012 (vol. 18 no. 9)
pp. 1460-1473
A. A. Goshtasby, Dept. of Comput. Sci. & Eng., Wright State Univ., Dayton, OH, USA
L. G. Zagorchev, Thayer Sch. of Eng., Dartmouth Coll., Hanover, NH, USA
A curvature-adaptive implicit surface reconstruction for noisy and irregularly spaced points in 3D is introduced. The reconstructed surface traces the zero crossings of a signed field obtained from the sum of first-derivative anisotropic Gaussians centered at the points. The standard deviations of the anisotropic Gaussians are adapted to surface curvatures estimated from local data. A key characteristic of the formulation is its ability to smooth more along edges than across them, thereby preserving shape details while smoothing noise. The behavior of the proposed method under various density and organization of points is investigated and surface reconstruction results are compared with those obtained by well-known methods in the literature.

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Index Terms:
solid modelling,Gaussian processes,smoothing methods,computer graphics,curvature-adaptive implicit surface reconstruction,irregularly spaced points,noisy spaced points,3D surface reconstruction,signed field zero crossings,first-derivative anisotropic Gaussians,standard deviations,surface curvatures,local data,shape details preservation,noise smoothing,Surface reconstruction,Surface treatment,Shape,Image reconstruction,Smoothing methods,Surface roughness,Rough surfaces,smoothness parameter.,Computer graphics,surface reconstruction,implicit surface,point cloud
Citation:
A. A. Goshtasby, L. G. Zagorchev, "A Curvature-Adaptive Implicit Surface Reconstruction for Irregularly Spaced Points," IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 9, pp. 1460-1473, Sept. 2012, doi:10.1109/TVCG.2011.276
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