Volume 29, Issue 6 pp. 1905-1920

Hierarchical Structure Recovery of Point-Sampled Surfaces

Marco Attene

Marco Attene

Istituto di Matematica Applicata e Tecnologie Informatiche, Consiglio Nazionale delle Ricerche, Italy [email protected] , [email protected]

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Giuseppe Patanè

Giuseppe Patanè

Istituto di Matematica Applicata e Tecnologie Informatiche, Consiglio Nazionale delle Ricerche, Italy [email protected] , [email protected]

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First published: 14 September 2010
Citations: 27

Abstract

We focus on the class of ‘regular’ models defined by Várady et al. for reverse engineering purposes. Given a 3D surface inline image represented through a dense set of points, we present a novel algorithm that converts inline image to a hierarchical representation inline image. In inline image, the surface is encoded through patches of various shape and size, which form a hierarchical atlas. If inline image belongs to the class of regular models, then inline image captures the most significant features of inline image at all the levels of detail. In this case, we show that inline image can be exploited to interactively select regions of interest on inline image and intuitively re-design the model. Furthermore, inline image intrinsically encodes a hierarchy of useful ‘segmentations’ of inline image. We present a simple though efficient approach to extract and optimize such segmentations, and we show how they can be used to approximate the input point sets through idealized manifold meshes.

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