Power Diagram Enhanced Adaptive Isosurface Extraction From Signed Distance Fields

Area of Science:

• Computer Graphics
• Computational Geometry
• Geometric Modeling

Background:

• Extracting high-fidelity mesh surfaces from Signed Distance Fields (SDFs) is crucial in geometry processing.
• Existing methods struggle to capture intricate geometric and topological structures within SDFs.
• Automating the extraction of complex surfaces from SDFs remains a significant challenge.

Purpose of the Study:

• To present a novel isosurface extraction algorithm for Signed Distance Fields.
• To address the challenge of capturing intricate geometric and topological structures.
• To improve the accuracy and efficiency of mesh surface extraction from SDFs.

Main Methods:

• An incrementally constructed power diagram using added sample points.
• Dual-regular Delaunay tetrahedralization for repeated surface updates.
• An adaptive point insertion strategy to refine mesh discrepancies.

Main Results:

• The proposed framework progressively refines the extracted mesh with minimal computational cost.
• Demonstrated superior performance compared to state-of-the-art methods.
• Successfully captured intricate geometric variations and complex topologies.

Conclusions:

• The novel algorithm effectively extracts high-fidelity mesh surfaces from SDFs.
• The method offers significant improvements for complex geometric and topological structures.
• This approach advances the field of geometry processing for detailed surface reconstruction.