This paper describes how a visual system can automatically define features of interest from the observation of a large enough number of natural images. The principle complements t...
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 ...
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...
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...
Eye gaze and gesture form key conversational grounding cues that are used extensively in face-to-face interaction among people. To accurately recognize visual feedback during inter...