Adaptive multi-scale analysis for point-based surface editing

Georges Nader 1, * G. Guennebaud 2, 3, 4 Nicolas Mellado 5
* Auteur correspondant
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
5 Smart Geometry Processing Group
Department of Computer Science
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.
Type de document :
Article dans une revue
Computer Graphics Forum, Wiley, 2014, pp.9. 〈10.1111/cgf.12485〉
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https://hal.inria.fr/hal-01059392
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Soumis le : mercredi 29 mars 2017 - 17:56:47
Dernière modification le : mercredi 5 avril 2017 - 01:10:15

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Georges Nader, G. Guennebaud, Nicolas Mellado. Adaptive multi-scale analysis for point-based surface editing. Computer Graphics Forum, Wiley, 2014, pp.9. 〈10.1111/cgf.12485〉. 〈hal-01059392〉

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