Ladeuil, MathieuTrabucato, MarcVaisse, AlexisFaraj, NouraGünther, TobiasMontazeri, Zahra2025-05-092025-05-092025978-3-03868-269-11017-4656https://doi.org/10.2312/egp.20251025https://diglib.eg.org/handle/10.2312/egp20251025In computer graphics, mesh clustering is a key component of various applications such as shape matching or skinning weight computation, especially when using hierarchical clustering. Garland et al. [GWH01] proposed to build a hierarchy of clusters by simplifying the dual graph of the mesh. We extend their method to provide control over cluster shapes through a combination of error metrics. Additionally, we alleviate the challenging task of finding an optimal threshold (stopping criterion) by considering a weighted feature graph that incorporates persistent cluster information throughout the hierarchy.Attribution 4.0 International License10.2312/egp.202510252 pages