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» Spatially Coherent Clustering Using Graph Cuts
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98
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CVPR
2004
IEEE
16 years 1 months ago
Spatially Coherent Clustering Using Graph Cuts
Feature space clustering is a popular approach to image segmentation, in which a feature vector of local properties (such as intensity, texture or motion) is computed at each pixe...
Ramin Zabih, Vladimir Kolmogorov
MICCAI
2004
Springer
16 years 1 days ago
Clustering Fiber Traces Using Normalized Cuts
In this paper we present a framework for unsupervised segmentation of white matter fiber traces obtained from diffusion weighted MRI data. Fiber traces are compared pairwise to cre...
Anders Brun, Hans Knutsson, Hae-Jeong Park, Martha...
228
Voted
PAMI
2010
396views more  PAMI 2010»
14 years 9 months ago
Self-Validated Labeling of Markov Random Fields for Image Segmentation
—This paper addresses the problem of self-validated labeling of Markov random fields (MRFs), namely to optimize an MRF with unknown number of labels. We present graduated graph c...
Wei Feng, Jiaya Jia, Zhi-Qiang Liu
ICCV
2011
IEEE
13 years 11 months ago
Recursive MDL via Graph Cuts: Application to Segmentation
We propose a novel patch-based image representation that is useful because it (1) inherently detects regions with repetitive structure at multiple scales and (2) yields a paramete...
Lena Gorelick, Andrew Delong, Olga Veksler, Yuri B...
DICTA
2003
15 years 17 days ago
Two-Level Image Segmentation Based on Region and Edge Integration
Abstract. This paper introduces a two-level approach for image segmentation based on region and edge integration. Edges are first detected in the original image using a combinatio...
Qing Wu, Yizhou Yu