SCALESPACE 2007 - PDF Preprint Papers

SCALESPACE 2007 International Conference on Scale-Space Theories in Computer Vision

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SCALESPACE
2007
Springer

350views Computer Vision» more SCALESPACE 2007»

Piecewise Constant Level Set Method for 3D Image Segmentation

14 years 5 months ago

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Level set methods have been proven to be eﬃcient tools for tracing interface problems. Recently, some variants of the Osher- Sethian level set methods, which are called the Piece...

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Id	Views	Title	Status

1	350	Piecewise Constant Level Set Method for 3D Image Segmentation	claim
2	297	Motion Compensated Video Super Resolution	claim
3	291	Faithful Recovery of Vector Valued Functions from Incomplete Data	claim
4	289	Level Set Methods for Watershed Image Segmentation	claim
5	260	Bayesian Non-local Means Filter, Image Redundancy and Adaptive Dictionaries for Noise Removal	claim
6	258	3D Object Recognition by Eigen-Scale-Space of Contours	claim
7	256	A Geometric-Functional-Based Image Segmentation and Inpainting	claim
8	247	Non-negative Sparse Modeling of Textures	claim
9	243	Uniform and Textured Regions Separation in Natural Images Towards MPM Adaptive Denoising	claim
10	224	Space-Time Segmentation Based on a Joint Entropy with Estimation of Nonparametric Distributions
11	213	On the Statistical Interpretation of the Piecewise Smooth Mumford-Shah Functional	claim
12	204	Fuzzy Region Competition: A Convex Two-Phase Segmentation Framework	claim
13	197	Combining Curvature Motion and Edge-Preserving Denoising	claim
14	188	Segmentation Under Occlusions Using Selective Shape Prior	claim
15	187	Towards Segmentation Based on a Shape Prior Manifold	claim
16	186	A Consistent Spatio-temporal Motion Estimator for Atmospheric Layers	claim
17	177	Best Basis Compressed Sensing	claim
18	175	Bounds on the Minimizers of (nonconvex) Regularized Least-Squares	claim
19	168	Super-Resolution Using Sub-band Constrained Total Variation	claim
20	157	Discrete Regularization on Weighted Graphs for Image and Mesh Filtering	claim
21	152	Dense Optical Flow Estimation from the Monogenic Curvature Tensor	claim
22	150	Total Variation Minimization and Graph Cuts for Moving Objects Segmentation	claim
23	150	Scale Spaces on Lie Groups	claim
24	150	Vector-Valued Image Interpolation by an Anisotropic Diffusion-Projection PDE	claim
25	147	A Geometric Variational Framework for Simultaneous Registration and Parcellation of Homologous Surfaces	claim
26	147	Histogram Based Segmentation Using Wasserstein Distances	claim
27	147	Detecting Regions of Dynamic Texture	claim
28	144	Mumford-Shah Regularizer with Spatial Coherence	claim
29	142	Beauty with Variational Methods: An Optic Flow Approach to Hairstyle Simulation	claim
30	141	New Possibilities with Sobolev Active Contours	claim
31	140	Modeling Foveal Vision	claim
32	139	Restoration of Images with Piecewise Space-Variant Blur	claim
33	139	Combining Different Types of Scale Space Interest Points Using Canonical Sets	claim
34	137	Iterated Nonlocal Means for Texture Restoration	claim
35	133	A Generic Approach to the Filtering of Matrix Fields with Singular PDEs	claim
36	131	The Variational Origin of Motion by Gaussian Curvature	claim
37	129	A Variational Approach for 3D Motion Estimation of Incompressible PIV Flows	claim
38	125	Identification of Grain Boundary Contours at Atomic Scale	claim
39	125	Paretian Similarity for Partial Comparison of Non-rigid Objects	claim
40	123	Numerical Invariantization for Morphological PDE Schemes	claim
41	114	Direct Shape-from-Shading with Adaptive Higher Order Regularisation	claim
42	110	A Variational Approach for Multi-valued Velocity Field Estimation in Transparent Sequences	claim
43	104	Spatio-temporal Scale-Spaces	claim
44	99	Linear Image Reconstruction by Sobolev Norms on the Bounded Domain	claim

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