Generalized edge-weighted centroidal Voronoi tessellations for geometry processing
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Publication:356224
DOI10.1016/j.camwa.2012.07.011zbMath1268.65029OpenAlexW2159915701MaRDI QIDQ356224
Lili Ju, Desheng Wang, Yu Wang, Xiaoqiang Wang
Publication date: 25 July 2013
Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.camwa.2012.07.011
surface reconstructionedge-weighted centroidal Voronoi tessellationsfeature preservingsurface smoothing
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High-quality 2D mesh generation without obtuse and small angles, Representing implicit surfaces satisfying Lipschitz conditions by 4-dimensional point sets
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Cites Work
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- Nonlinear total variation based noise removal algorithms
- Geometric applications of the split Bregman method: segmentation and surface reconstruction
- Adaptive variational curve smoothing based on level set method
- Fronts propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulations
- Geodesic active contours
- Surface reconstruction by Voronoi filtering
- A phase field approach in the numerical study of the elastic bending energy for vesicle membranes
- A variational phase field method for curve smoothing
- Centroidal Voronoi tessellation algorithms for image compression, segmentation, and multichannel restoration
- Simulating the deformation of vesicle membranes under elastic bending energy in three dimensions
- Variational surface reconstruction based on Delaunay triangulation and graph cut
- Optimal approximations by piecewise smooth functions and associated variational problems
- Advances in Studies and Applications of Centroidal Voronoi Tessellations
- Edge-Weighted Centroidal Voronoi Tessellations
- A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
- Graph Cut Optimization for the Piecewise Constant Level Set Method Applied to Multiphase Image Segmentation
- A fast sweeping method for Eikonal equations
- Centroidal Voronoi Tessellations: Applications and Algorithms
- Least squares quantization in PCM
- An Edge-Weighted Centroidal Voronoi Tessellation Model for Image Segmentation
- Image Segmentation Using Local Variation and Edge-Weighted Centroidal Voronoi Tessellations
- Bregman Iterative Algorithms for $\ell_1$-Minimization with Applications to Compressed Sensing
- Convergence of the Lloyd Algorithm for Computing Centroidal Voronoi Tessellations
- Scale Recognition, Regularization Parameter Selection, and Meyer's G Norm in Total Variation Regularization
