Presentation
Dual Contouring of Signed Distance Data
DescriptionWe propose an algorithm to reconstruct explicit polygonal meshes from discretely sampled Signed Distance Function (SDF) data, which is especially effective at recovering sharp features. Building on the Dual Contouring of Hermite Data method, we solve a quadratic optimization problem to place the mesh's vertices. Critically, this optimization relies solely on discretely sampled SDF data, without requiring arbitrary access to the function, gradient information, or training on large-scale datasets. Our method sets a new state of the art in surface reconstruction from SDFs at medium and high resolutions, and opens the door for applications in 3D modeling and design.
Event Type
Technical Paper
TimeMonday, 20 July 20264:25pm - 4:35pm PDT
LocationRoom 408 B
Digital Library
PDF
Session Time & Location
Sunday, 19 July 20266:00pm - 8:45pm PDTHall K
Monday, 20 July 20263:45pm - 5:35pm PDTRoom 408 B
Geometry
Modeling
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