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dc.contributor.authorBoulch, Alexandreen_US
dc.contributor.authorHoullier, Simonen_US
dc.contributor.authorMarlet, Renauden_US
dc.contributor.authorTournaire, Olivieren_US
dc.contributor.editorYaron Lipman and Hao Zhangen_US
dc.date.accessioned2015-02-28T15:50:29Z
dc.date.available2015-02-28T15:50:29Z
dc.date.issued2013en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/cgf.12170en_US
dc.description.abstractWe 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.en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subjectI.2.10 [Artificial Intelligence]en_US
dc.subjectVision and Scene Understandingen_US
dc.subject3D/stereo scene analysisen_US
dc.subjectI.3.5 [Computer Graphics]en_US
dc.subjectComputational Geometry and Object Modelingen_US
dc.subjectObject hierarchiesen_US
dc.subjectI.4.8 [Image Processing and Computer Vision]en_US
dc.subjectScene Analysisen_US
dc.subjectObject recognitionen_US
dc.subjectI.5.4 [Pattern Recognition]en_US
dc.subjectApplicationsen_US
dc.subjectComputer visionen_US
dc.titleSemantizing Complex 3D Scenes using Constrained Attribute Grammarsen_US
dc.description.seriesinformationComputer Graphics Forumen_US


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