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130
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CVPR
2003
IEEE
16 years 4 months ago
Video Segmentation Based on Graphical Models
This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field...
Kia-Fock Loe, Tele Tan, Yang Wang 0002
116
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COLING
2010
14 years 9 months ago
TimeML Events Recognition and Classification: Learning CRF Models with Semantic Roles
This paper analyzes the contribution of semantic roles to TimeML event recognition and classification. For that purpose, an approach using conditional random fields with a variety...
Hector Llorens, Estela Saquete, Borja Navarro-Colo...
SIAMIS
2010
378views more  SIAMIS 2010»
14 years 9 months ago
Global Interactions in Random Field Models: A Potential Function Ensuring Connectedness
Markov random field (MRF) models, including conditional random field models, are popular in computer vision. However, in order to be computationally tractable, they are limited to ...
Sebastian Nowozin, Christoph H. Lampert
138
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ECCV
2008
Springer
16 years 4 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
INFORMATICALT
2006
150views more  INFORMATICALT 2006»
15 years 2 months ago
A Multiresolution Approach Based on MRF and Bak-Sneppen Models for Image Segmentation
The two major Markov Random Fields (MRF) based algorithms for image segmentation are the Simulated Annealing (SA) and Iterated Conditional Modes (ICM). In practice, compared to the...
Kamal E. Melkemi, Mohamed Batouche, Sebti Foufou