Image-based rendering data sets, such as light fields, require efficient compression due to their large data size, but also easy random access when rendering from the data set. Ef...
This is the sample implementation of a Markov random field based image segmentation algorithm described in the following papers:
1. Mark Berthod, Zoltan Kato, Shan Yu, and Josi...
We propose a means of extending Conditional Random Field modeling to decision-theoretic planning where valuation is dependent upon fullyobservable factors. Representation is discu...
This work relates to the implementation of a 2D conditional random field model in the context of document image analysis. Our model makes it possible to take variability into acco...
We describe a probabilistic approach to content selection for meeting summarization. We use skipchain Conditional Random Fields (CRF) to model non-local pragmatic dependencies bet...