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DTSTAMP:20260817T171533Z
LOCATION:Hall B5 (1)\, B Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241206T134200
DTEND;TZID=Asia/Tokyo:20241206T135600
UID:siggraphasia_SIGGRAPH Asia 2024_sess145_papers_960@linklings.com
SUMMARY:SING: Stability-Incorporated Neighborhood Graph
DESCRIPTION:Diana Marin (Technical University of Vienna); Amal Dev Parakka
 t (LTCI, Telecom ParisTech; Institut Polytechnique de Paris); Stefan Ohrha
 llinger and Michael Wimmer (Technical University of Vienna); Steve Oudot (
 Institut national de recherche en informatique et en automatique (INRIA));
  and Pooran Memari (CNRS, Inria, LIX; École Polytechnique, IP-Paris)\n\nWe
  introduce the Stability-Incorporated Neighborhood Graph (SING), a novel d
 ensity-aware structure designed to capture the intrinsic geometric propert
 ies of a point set. We improve upon the spheres-of-influence graph by inco
 rporating additional features to offer more flexibility and control in enc
 oding proximity information and capturing local density variations. Throug
 h persistence analysis on our proximity graph, we propose a new clustering
  technique and explore additional variants incorporating extra features fo
 r the proximity criterion. Alongside the detailed analysis and comparison 
 to evaluate its performance on various datasets, our experiments demonstra
 te that the proposed method can effectively extract meaningful clusters fr
 om diverse datasets with variations in density and correlation. Our applic
 ation scenarios underscore the advantages of the proposed graph over class
 ical neighborhood graphs, particularly in terms of parameter tuning.\n\nRe
 gistration Category: Full Access, Full Access Supporter\n\nLanguage Format
 : English Language\n\nSession Chair: Hao (Richard) Zhang (Simon Fraser Uni
 versity, Augmenta)\n\n
URL:https://asia.siggraph.org/2024/program/?id=papers_960&sess=sess145
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