This paper shows that the basic Hough transform is implicitly a Bayesian process--that it computes an unnormalized posterior distribution over the parameters of a single shape giv...
Neil Toronto, Bryan S. Morse, Dan Ventura, Kevin D...
We develop a Bayesian model of digitized archival films and use this for denoising, or more specifically de-graining, individual frames. In contrast to previous approaches our mod...
Teodor Mihai Moldovan, Stefan Roth, Michael J. Bla...
In this paper, we propose two Bayesian methods for detecting and grouping junctions. Our junction detection method evolves from the Kona approach, and it is based on a competitive ...
Miguel Cazorla, Francisco Escolano, Domingo Gallar...
Previous research on automatic image annotation has shown that accurate estimates of the class conditional densities in generative models have a positive effect in annotation perf...
This paper describes a supervised segmentation algorithm which draws inspiration from recent advances in non-parametric texture synthesis. A set of example images which have been ...