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Total variation diffusion and its application in shape decomposition
- Source :
- Computers & Graphics. 90:95-107
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- One challenge in shape decomposition is to capture correct boundaries between different parts and get piecewise constant results. Based on the good edge-preserving and sparsity properties of total variation regularization, this paper introduces a novel diffusion model by minimizing weighted total-variation energy with Dirichlet boundary constraints. By the total variation diffusion model, we propose an edge-preserving shape decomposition optimization model, which can be solved effectively by augmented Lagrangian method with each subproblem having closed form solution. A number of experiments display that our method can produce segmentation results with piecewise constant parts and feature-preserving boundaries for both meshes and 3D point clouds, especially for shapes with sharp features. In addition, for mesh segmentation, our results compare favorably to those obtained by several existing techniques when evaluated on the Princeton Segmentation Benchmark. Furthermore, the quantitative errors show that the algorithm is robust numerically and the computational costs are reasonable.
- Subjects :
- Augmented Lagrangian method
General Engineering
020207 software engineering
02 engineering and technology
Total variation denoising
Computer Graphics and Computer-Aided Design
Human-Computer Interaction
0202 electrical engineering, electronic engineering, information engineering
Piecewise
Applied mathematics
020201 artificial intelligence & image processing
Segmentation
Polygon mesh
Closed-form expression
Diffusion (business)
Constant (mathematics)
Mathematics
Subjects
Details
- ISSN :
- 00978493
- Volume :
- 90
- Database :
- OpenAIRE
- Journal :
- Computers & Graphics
- Accession number :
- edsair.doi...........a4896530fedf741c12b50aae997812a0