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ICPR
2002
IEEE
14 years 8 months ago
Multicue MRF Image Segmentation: Combining Texture and Color Features
Herein, we propose a new Markov random field (MRF) image segmentation model which aims at combining color and texture features. The model has a multi-layer structure: Each feature...
Zoltan Kato, Ting-Chuen Pong, Song Guo Qiang
ICIG
2009
IEEE
13 years 5 months ago
Statistical Modeling of Optical Flow
Optical flow estimation is one of the main subjects in computer vision. Many methods developed to compute the motion fields are built using standard heuristic formulation. In this...
Dongmin Ma, Véronique Prinet, Cyril Cassisa
MICCAI
2008
Springer
14 years 8 months ago
MRI Bone Segmentation Using Deformable Models and Shape Priors
Abstract. This paper addresses the problem of automatically segmenting bone structures in low resolution clinical MRI datasets. The novel aspect of the proposed method is the combi...
Jérôme Schmid, Nadia Magnenat-Thalman...
ACCV
2006
Springer
14 years 1 months ago
Markovian Framework for Foreground-Background-Shadow Separation of Real World Video Scenes
Abstract. In this paper we give a new model for foreground-background-shadow separation. Our method extracts the faithful silhouettes of foreground objects even if they have partly...
Csaba Benedek, Tamás Szirányi
UAI
2008
13 years 9 months ago
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
John Duchi, Stephen Gould, Daphne Koller