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» Markov Random Field Modeling in Computer Vision
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CVPR
2009
IEEE
15 years 2 months ago
Learning Optimized MAP Estimates in Continuously-Valued MRF Models
We present a new approach for the discriminative training of continuous-valued Markov Random Field (MRF) model parameters. In our approach we train the MRF model by optimizing t...
Kegan G. G. Samuel, Marshall F. Tappen
ECCV
2008
Springer
14 years 9 months ago
Learning for Optical Flow Using Stochastic Optimization
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
Yunpeng Li, Daniel P. Huttenlocher
ICCV
2009
IEEE
13 years 5 months ago
Analysis of orientation and scale in smoothly varying textures
We present a novel representation for modeling textured regions subject to smooth variations in orientation and scale. Utilizing the steerable pyramid of Simoncelli and Freeman as...
Jason Chang, John W. Fisher III
BMVC
2010
13 years 5 months ago
Motion Coherent Tracking with Multi-label MRF optimization
We present a novel off-line algorithm for target segmentation and tracking in video. In our approach, video data is represented by a multi-label Markov Random Field model, and seg...
David Tsai, Matthew Flagg, James M. Rehg
CVPR
2000
IEEE
14 years 9 months ago
Learning in Gibbsian Fields: How Accurate and How Fast Can It Be?
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
Song Chun Zhu, Xiuwen Liu