18 search results - page 3 / 4 » Inconsistent parameter estimation in Markov random fields: B... |
CVPR
2000
IEEE
14 years 8 months ago
2000
IEEE
?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...
ECCV
2008
Springer
14 years 8 months ago
2008
Springer
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...
ECCV
2006
Springer
14 years 8 months ago
2006
Springer
Abstract. We formulate a robust method using Expectation Maximization (EM) to address the problem of dense photometric stereo. Previous approaches using Markov Random Fields (MRF) ...
MICCAI
2010
Springer
13 years 4 months ago
2010
Springer
In this paper we introduce a novel approach for inferring articulated spine models from images. A low-dimensional manifold embedding is created from a training set of prior mesh mo...
ECCV
2004
Springer
14 years 8 months ago
2004
Springer
The problem of interactive foreground/background segmentation in still images is of great practical importance in image editing. The state of the art in interactive segmentation is...