Semantizing Complex 3D Scenes using Constrained Attribute Grammars - École des Ponts ParisTech Access content directly
Journal Articles Computer Graphics Forum Year : 2013

Semantizing Complex 3D Scenes using Constrained Attribute Grammars

Abstract

We propose a new approach to automatically semantize complex objects in a 3D scene. For this, we define an expressive formalism combining the power of both attribute grammars and constraint. It offers a practical conceptual interface, which is crucial to write large maintainable specifications. As recursion is inadequate to express large collections of items, we introduce maximal operators, that are essential to reduce the parsing search space. Given a grammar in this formalism and a 3D scene, we show how to automatically compute a shared parse forest of all interpretations -- in practice, only a few, thanks to relevant constraints. We evaluate this technique for building model semantization using CAD model examples as well as photogrammetric and simulated LiDAR data.
Fichier principal
Vignette du fichier
SGP-2013-Boulch-et-al (1).pdf (4.63 Mo) Télécharger le fichier
SGP-2013-Boulch-et-al_slides.pdf (5.81 Mo) Télécharger le fichier
SGP-2013-Boulch-et-al_supp.pdf (5.06 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-00864707 , version 1 (22-02-2019)

Identifiers

Cite

Alexandre Boulch, Simon Houllier, Renaud Marlet, Olivier Tournaire. Semantizing Complex 3D Scenes using Constrained Attribute Grammars. Computer Graphics Forum, 2013, 32 (5), pp.33-42. ⟨10.1111/cgf.12170⟩. ⟨hal-00864707⟩
421 View
430 Download

Altmetric

Share

Gmail Facebook X LinkedIn More