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Semantizing complex 3D scenes using constrained attribute grammars

  • A. Boulch
  • , S. Houllier
  • , R. Marlet
  • , O. Tournaire
  • Université Paris-Est
  • CSTB

Research output: Contribution to conferencePaperpeer-review

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.

Original languageEnglish
Pages33-42
Number of pages10
DOIs
Publication statusPublished - 3 Jul 2013
Externally publishedYes
Event11th Eurographics/ACM SIGGRAPH Symposium on Geometry Processing, SGP 2013 - Genova, Italy
Duration: 3 Jul 20135 Jul 2013

Conference

Conference11th Eurographics/ACM SIGGRAPH Symposium on Geometry Processing, SGP 2013
Country/TerritoryItaly
CityGenova
Period3/07/135/07/13

Keywords

  • 3D/stereo scene analysis I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling
  • Categories and Subject Descriptors (according to ACM CCS): I.2.10 [Artificial Intelligence]: Vision and Scene Understanding
  • Computer vision
  • Object hierarchies I.4.8 [Image Processing and Computer Vision]: Scene Analysis
  • Object recognition I.5.4 [Pattern Recognition]: Applications

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