Inference of geometric modeling operations
Apr 4, 2023·
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1 min read
Romain Pascual
Hakim Belhaouari
Pascale Le Gall
Agnès Arnould
Abstract
Implementing new geometric modelling operations can be challenging. However, their description can be easily understood from a sketch or an example. We propose a method to infer operations from a representative example consisting of an initial and a target object. The inference mechanism exploits the regularity of generalised maps and Jerboa’s rule-based language for the reconstruction of the topology. The inference of geometric aspects considers affine transformations of values from a vector space, which we solve as a constraint satisfaction problem.
Event
Location
Université Paris-Cité
Presentation of a poster at the Journées Nationales de l’Informatique Mathématique 2023 following the prize obtained at the GT Modélisation Géométrique in 2022.
Abstract: Implementing new geometric modelling operations can be challenging. However, their description can be easily understood from a sketch or an example. We propose a method to infer operations from a representative example consisting of an initial and a target object. The inference mechanism exploits the regularity of generalised maps and Jerboa’s rule-based language for the reconstruction of the topology. The inference of geometric aspects considers affine transformations of values from a vector space, which we solve as a constraint satisfaction problem.
