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» Supervised Image Segmentation Using Markov Random Fields
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1851views
17 years 2 months ago
Cerebrovascular Segmentation from TOF Using Stochastic Models
In this paper, we present an automatic statistical approach for extracting 3D blood vessels from time-of-flight (TOF) magnetic resonance angiography (MRA) data. The voxels of the d...
M. Sabry Hassouna, Aly A. Farag, Stephen Hushek, T...
ECCV
2006
Springer
16 years 3 months ago
PoseCut: Simultaneous Segmentation and 3D Pose Estimation of Humans Using Dynamic Graph-Cuts
Abstract. We present a novel algorithm for performing integrated segmentation and 3D pose estimation of a human body from multiple views. Unlike other related state of the art tech...
Matthieu Bray, Pushmeet Kohli, Philip H. S. Torr
PAMI
2002
108views more  PAMI 2002»
15 years 1 months ago
Approximate Bayes Factors for Image Segmentation: The Pseudolikelihood Information Criterion (PLIC)
We propose a method for choosing the number of colors or true gray levels in an image; this allows fully automatic segmentation of images. Our underlying probability model is a hid...
Derek C. Stanford, Adrian E. Raftery
IBPRIA
2007
Springer
15 years 7 months ago
Bayesian Oil Spill Segmentation of SAR Images Via Graph Cuts
Abstract. This paper extends and generalizes the Bayesian semisupervised segmentation algorithm [1] for oil spill detection using SAR images. In the base algorithm on which we buil...
Sónia Pelizzari, José M. Bioucas-Dia...
INTERSPEECH
2010
14 years 8 months ago
Deep-structured hidden conditional random fields for phonetic recognition
We extend our earlier work on deep-structured conditional random field (DCRF) and develop deep-structured hidden conditional random field (DHCRF). We investigate the use of this n...
Dong Yu, Li Deng