Simplification of 2D Polygonal Partitions via Point‐line Projective Duality, and Application to Urban Reconstruction - Inria - Institut national de recherche en sciences et technologies du numérique
Article Dans Une Revue Computer Graphics Forum Année : 2022

Simplification of 2D Polygonal Partitions via Point‐line Projective Duality, and Application to Urban Reconstruction

Résumé

We address the problem of simplifying two-dimensional polygonal partitions that exhibit strong regularities. Such partitions are relevant for reconstructing urban scenes in a concise way. Preserving long linear structures spanning several partition cells motivates a point-line projective duality approach in which points represent line intersections, and lines possibly carry multiple points. We propose a simplification algorithm that seeks a balance between the fidelity to the input partition, the enforcement of canonical relationships between lines (orthogonality or parallelism) and a low complexity output. Our methodology alternates continuous optimization by Riemannian gradient descent with combinatorial reduction, resulting in a progressive simplification scheme. Our experiments show that preserving canonical relationships helps gracefully degrade partitions of urban scenes, and yields more concise and regularity-preserving meshes than common mesh-based simplification approaches.
Fichier principal
Vignette du fichier
cgf-simp-2022.pdf (4.95 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03661872 , version 1 (08-05-2022)

Identifiants

Citer

Julien Vuillamy, André Lieutier, Florent Lafarge, Pierre Alliez. Simplification of 2D Polygonal Partitions via Point‐line Projective Duality, and Application to Urban Reconstruction. Computer Graphics Forum, 2022, ⟨10.1111/cgf.14511⟩. ⟨hal-03661872⟩
143 Consultations
315 Téléchargements

Altmetric

Partager

More