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BEGIN:VEVENT
DTSTAMP:20250110T023312Z
LOCATION:Hall B5 (1)\, B Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241205T092300
DTEND;TZID=Asia/Tokyo:20241205T093400
UID:siggraphasia_SIGGRAPH Asia 2024_sess124_papers_173@linklings.com
SUMMARY:MATTopo: Topology-preserving Medial Axis Transform with Restricted
  Power Diagram
DESCRIPTION:Technical Papers\n\nNingna Wang (University of Texas at Dallas
 ), Hui Huang (Shenzhen University (SZU)), Shibo Song (Independent Research
 er), Bin Wang (Tsinghua University), Wenping Wang (Texas A&M University), 
 and Xiaohu Guo (University of Texas at Dallas)\n\nWe present a novel topol
 ogy-preserving 3D medial axis computation framework based on volumetric re
 stricted power diagram (RPD), while preserving the medial features and geo
 metric convergence simultaneously, for both 3D CAD and organic shapes. The
  volumetric RPD discretizes the input 3D volume into sub-regions given a s
 et of medial spheres. With this intermediate structure, we convert the hom
 otopy equivalency between the generated medial mesh and the input 3D shape
  into a localized contractibility checking for each restricted element (po
 wer cell, power face, power edge), by checking their connected components 
 and Euler characteristics. We further propose a fractional Euler character
 istic algorithm for efficient GPU-based computation of Euler characteristi
 c for each restricted element on the fly while computing the volumetric RP
 D. Compared with existing voxel-based or point-cloud-based methods, our ap
 proach is the first to adaptively and directly revise the medial mesh with
 out globally modifying the dependent structure, such as voxel size or samp
 ling density, while preserving its topology and medial features. In compar
 ison with the feature preservation method MATFP, our method provides geome
 trically comparable results with fewer spheres and more robustly captures 
 the topology of the input 3D shape.\n\nRegistration Category: Full Access,
  Full Access Supporter\n\nLanguage Format: English Language\n\nSession Cha
 ir: Yotam Gingold (George Mason University)
URL:https://asia.siggraph.org/2024/program/?id=papers_173&sess=sess124
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