Title:
SpectralSurfaceReconstructionfromNoisyPointClouds.
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Description: We introduce a noise-resistant algorithm for reconstructing a watertight surface from point cloud data.
It forms a Delaunay tetrahedralization, then uses a variant of spectral graph partitioning to decide whether each
tetrahedron is inside or outside the original object. The reconstructed surface triangulation is the set of triangular
faces where inside and outside tetrahedra meet. Because the spectral partitioner makes local decisions based on
a global view of the model, it can ignore outliers, patch holes and undersampled regions, and surmount ambiguity
due to measurement errors. Our algorithm can optionally produce a manifold surface. We present empirical
evidence that our implementation is substantially more robust than several closely related surface reconstruction
programs.
- [3Ddemodemonstrationprogram.Rar] - write his point of the three-dimensional
- [3DDelaunay] - using C and OpenGL-based growth method t
- [Fluid] - 2D real-time fluid dynamics simulation,
- [manifold] - Manifold learning algorithm library, inc
- [vtk5] - 3d reconstruction of the surface renderi
- [ear2] - The multi-view Ear Recognition Based on
- [triangle++.tar] - this a visual c++ code for point cloud t
- [segmentation] - This paper provides an algorithm for par
- [Meshgeomview-1.9.4.tar] - pour la triangulation,les fichier en c++
- [SGT] - Spectral Graph Theory Spectrum classic t
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SpectralSurfaceReconstructionfromNoisyPointClouds.pdf
