Semantic correspondence across 3D models for example-based modeling

Vincent Léon (1) , Vincent Itier (2) , Nicolas Bonneel (3, 4) , Guillaume Lavoué (3) , Jean-Philippe Vandeborre (2, 5)

1 Uraniom
2 IMT Lille Douai - Ecole nationale supérieure Mines-Télécom Lille Douai
3 M2DisCo - Geometry Processing and Constrained Optimization
4 GeoMod - Modélisation Géométrique, Géométrie Algorithmique, Fractales
5 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189

Modeling 3D shapes is a specialized skill not affordable to most novice artists due to its complexity and tediousness. At the same time, databases of complex models ready for use are becoming widespread, and can help the modeling task in a process called example-based modeling. We introduce such an example-based mesh modeling approach which, contrary to prior work, allows for the replacement of any localized region of a mesh by a region of similar semantics (but different geometry) within a mesh database. For that, we introduce a selection tool in a space of semantic descriptors that co-selects areas of similar semantics within the database. Moreover, this tool can be used for part-based retrieval across the database. Then, we show how semantic information improves the assembly process. This allows for modeling complex meshes from a coarse geometry and a database of more detailed meshes, and makes modeling accessible to the novice user.

Mots clés: Computational Geometry and Object; Vision and Scene Understanding; Information Search and Retrieval; Search Process

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Géométrie algorithmique [cs.CG]

Vincent Léon, Vincent Itier, Nicolas Bonneel, Guillaume Lavoué, Jean-Philippe Vandeborre. Semantic correspondence across 3D models for example-based modeling. Eurographics Workshop on 3D Object Retrieval 2017 (3DOR 2017), Apr 2017, Lyon, France. 7 p. ⟨hal-01535056⟩