445 search results - page 30 / 89 » Learning Image Structures for Optimizing Disparity Estimatio... |
ECCV
2008
Springer
14 years 9 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...
ICCV
2009
IEEE
13 years 5 months ago
2009
IEEE
Many segmentation problems in medical imaging rely on accurate modeling and estimation of tissue intensity probability density functions. Gaussian mixture modeling, currently the ...
ICCV
2005
IEEE
14 years 9 months ago
2005
IEEE
Many computer vision algorithms limit their performance by ignoring the underlying 3D geometric structure in the image. We show that we can estimate the coarse geometric propertie...
ICIP
2006
IEEE
14 years 9 months ago
2006
IEEE
The automatic computation of features for content-based image retrieval still has difficulties to represent the concepts the user has in mind. Whenever an additional learning stra...
CVPR
2009
IEEE
15 years 2 months ago
2009
IEEE
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...