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Adaptive multi-scale analysis for point-based surface editing

Georges Nader 1, * Gael Guennebaud 2, 3, 4 Nicolas Mellado 5
* Corresponding author
1 M2DisCo - Geometry Processing and Constrained Optimization
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
4 MANAO - Melting the frontiers between Light, Shape and Matter
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest, LP2N - Laboratoire Photonique, Numérique et Nanosciences
Abstract : This paper presents a tool that enables the direct editing of surface features in large point-clouds or meshes. This is made possible by a novel multi-scale analysis of unstructured point-clouds that automatically extracts the number of relevant features together with their respective scale all over the surface. Then, combining this ingredient with an adequate multi-scale decomposition allows us to directly enhance or reduce each feature in an independent manner. Our feature extraction is based on the analysis of the scale-variations of locally fitted surface primitives combined with unsupervised learning techniques. Our tool may be applied either globally or locally, and millions of points are handled in real-time. The resulting system enables users to accurately edit complex geometries with minimal interaction.
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Submitted on : Wednesday, March 29, 2017 - 5:56:47 PM
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Georges Nader, Gael Guennebaud, Nicolas Mellado. Adaptive multi-scale analysis for point-based surface editing. Computer Graphics Forum, Wiley, 2014, 33, pp.9. ⟨10.1111/cgf.12485⟩. ⟨hal-01059392⟩

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