Piecewise Smooth Reconstruction of Normal Vector Field on Digital Data
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Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
We propose a novel method to regularize a normal vector field defined on a digital surface (boundary of a set of voxels). When the digital surface is a digitization of a piecewise smooth manifold, our method localizes sharp features (edges) while regularizing the input normal vector field at the same time. It relies on the optimisation of a variant of the Ambrosio-Tortorelli functional, originally defined for denoising and contour extraction in image processing [AT90]. We reformulate this functional to digital surface processing thanks to discrete calculus operators. Experiments show that the output normal field is very robust to digitization artifacts or noise, and also fairly independent of the sampling resolution. The method allows the user to choose independently the amount of smoothing and the length of the set of discontinuities. Sharp and vanishing features are correctly delineated even on extremely damaged data. Finally, our method can be used to enhance considerably the output of state-ofthe- art normal field estimators like Voronoi Covariance Measure [MOG11] or Randomized Hough Transform [BM12].
Description
@article{10.1111:cgf.13013,
journal = {Computer Graphics Forum},
title = {{Piecewise Smooth Reconstruction of Normal Vector Field on Digital Data}},
author = {Coeurjolly, David and Foare, Marion and Gueth, Pierre and Lachaud, Jacques-Olivier},
year = {2016},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.13013}
}