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DTSTAMP:20250110T023312Z
LOCATION:Hall B5 (1)\, B Block\, Level 5
DTSTART;TZID=Asia/Tokyo:20241205T091100
DTEND;TZID=Asia/Tokyo:20241205T092300
UID:siggraphasia_SIGGRAPH Asia 2024_sess124_papers_823@linklings.com
SUMMARY:Medial Skeletal Diagram: A Generalized Medial Axis Approach for 3D
  Shape Representation
DESCRIPTION:Technical Papers\n\nMinghao Guo, Bohan Wang, and Wojciech Matu
 sik (MIT CSAIL)\n\nWe propose the Medial Skeletal Diagram, a novel skeleta
 l representation that tackles the prevailing issues around skeleton sparsi
 ty and reconstruction accuracy in existing skeletal representations. Our a
 pproach augments the continuous elements in the medial axis representation
  to effectively shift the complexity away from the discrete elements. To t
 hat end, we introduce generalized enveloping primitives, an enhancement ov
 er the standard primitives in the medial axis, which ensure efficient cove
 rage of intricate local features of the input shape and substantially redu
 ce the number of discrete elements required. Moreover, we present a comput
 ational framework for constructing a medial skeletal diagram from an arbit
 rary closed manifold mesh. Our optimization pipeline ensures that the resu
 lting medial skeletal diagram comprehensively covers the input shape with 
 the fewest primitives. Additionally, each optimized primitive undergoes a 
 post-refinement process to guarantee an accurate match with the source mes
 h in both geometry and tessellation. We validate our approach on a compreh
 ensive benchmark of 100 shapes, demonstrating the sparsity of the discrete
  elements and superior reconstruction accuracy across a variety of cases. 
 Finally, we exemplify the versatility of our representation in downstream 
 applications such as shape generation, mesh decomposition, shape optimizat
 ion, mesh alignment, mesh compression, and user-interactive design.\n\nReg
 istration Category: Full Access, Full Access Supporter\n\nLanguage Format:
  English Language\n\nSession Chair: Yotam Gingold (George Mason University
 )
URL:https://asia.siggraph.org/2024/program/?id=papers_823&sess=sess124
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