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DTSTAMP:20260817T171516Z
LOCATION:Hall C\, C Block\, Level 4
DTSTART;TZID=Asia/Tokyo:20241203T090000
DTEND;TZID=Asia/Tokyo:20241203T120000
UID:siggraphasia_SIGGRAPH Asia 2024_sess223_papers_995@linklings.com
SUMMARY:Dynamic Skeletonization via Variational Medial Axis Sampling
DESCRIPTION:Qijia HUANG, Pierre KRAEMER, Sylvain THERY, and Dominique BECH
 MANN (Université de Strasbourg; ICube, CNRS)\n\nWe present a novel method 
 for computing a discrete skeleton from a shape represented by a point clou
 d or triangle mesh.\nInspired by variational shape approximation, our appr
 oach optimizes the partitioning of the input shape by minimizing an error 
 metric defined between medial axis samples (medial spheres) and their corr
 esponding clusters.\nThe metric combines plane-sphere and point-sphere dis
 tance terms and the balance between these two terms enables coarse skeleto
 ns to capture the main geometric features while denser skeletons achieve a
  uniform distribution of medial axis samples.\nThe sampling of the medial 
 axis is progressively refined through an automatic process that splits med
 ial spheres with the highest errors.\nOur method's efficiency also allows 
 users to dynamically add or remove medial axis samples locally while the o
 ptimization process continuously updates the underlying partition.\nSkelet
 on connectivity is efficiently constructed by computing the dual of the op
 timized shape partition.\nUnlike previous approaches, our method does not 
 rely on a predefined set of candidate spheres or an initial medial axis re
 presentation.\n\nRegistration Category: Enhanced Access, Full Access, Full
  Access Supporter\n\nLanguage Format: English Language\n\n
URL:https://asia.siggraph.org/2024/program/?id=papers_995&sess=sess124
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