Presentation

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ADS: Random Sampling of Occupancy Functions using Adaptive Delaunay Scaffolding
SessionWinding Numbers & Surface Representations
DescriptionWe present ADS, a method that delivers both pseudo-random surface samples and isosurface connectivity from occupancy functions, unlike prior approaches that typically provide only one. ADS achieves this with orders of magnitude fewer function evaluations at comparable accuracy than prior approaches, by progressively refining a Delaunay scaffold around the surface.
Authors
Suzuran Takikawa
The University of British Columbia
Leo Foord-Kelcey
The University of British Columbia
Oliver Oxford
The University of British Columbia
Nicholas Vining
NVIDIA
The University of British Columbia
Alla Sheffer
The University of British Columbia
Event Type
Technical Paper
TimeMonday, 20 July 202611:25am - 11:35am PDT
LocationRoom 403 A
Digital Library PDF
Session Time & Location
Sunday, 19 July 20266:00pm - 8:45pm PDTHall K
Monday, 20 July 202610:45am - 12:35pm PDTRoom 403 A
Keywords
Geometry
Modeling
Registration Categories
Full Conference Supporter
Full Conference
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