Proximity-Aware Multiple Meshes Decimation using Quadric Error Metric

Autor: Anahid Ghazanfarpour, Chems E. Himeur, Nicolas Mellado, Jean-Pierre Jessel, Loïc Barthe
Přispěvatelé: Structural Models and Tools in Computer Graphics (IRIT-STORM), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Centre National de la Recherche Scientifique (CNRS), Université Toulouse III - Paul Sabatier (UT3), Real Expression Artificial Life (IRIT-REVA)
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Graphical Models
Graphical Models, Elsevier, 2020, pp.101062. ⟨10.1016/j.gmod.2020.101062⟩
ISSN: 1524-0703
1524-0711
DOI: 10.1016/j.gmod.2020.101062⟩
Popis: International audience; Progressive mesh decimation by successive edge collapses is a standard tool in geometry processing. A key element of such algorithms is the error metric, which prioritizes the edge collapses to greedily minimize the simplification error. Most previous works focus on preserving local shape properties. However, meshes describing complex systems often require significant decimation for fast transmission and visualization on low-end terminals, and preserving the arrangement of objects is required to maintain the overall system readability for applications such as on-site repair, inspection, training, serious games, etc. We present a novel approach for the joint decimation of multiple triangular meshes. We combine local edge error (e.g. Quadric Error Metric) with a proximity-aware penalty function, which increases the error of edge collapses modifying the geometry in proximity areas. We propose an automatic detection of proximity areas and we demonstrate the performances of our approach on several models generated from CAD scenes.
Databáze: OpenAIRE