Sciweavers

Share
CVPR
2008
IEEE

(BP)2: Beyond pairwise Belief Propagation labeling by approximating Kikuchi free energies

10 years 6 months ago
(BP)2: Beyond pairwise Belief Propagation labeling by approximating Kikuchi free energies
Belief Propagation (BP) can be very useful and efficient for performing approximate inference on graphs. But when the graph is very highly connected with strong conflicting interactions, BP tends to fail to converge. Generalized Belief Propagation (GBP) provides more accurate solutions on such graphs, by approximating Kikuchi free energies, but the clusters required for the Kikuchi approximations are hard to generate. We propose a new algorithmic way of generating such clusters from a graph without exponentially increasing the size of the graph during triangulation. In order to perform the statistical region labeling, we introduce the use of superpixels for the nodes of the graph, as it is a more natural representation of an image than the pixel grid. This results in a smaller but much more highly interconnected graph where BP consistently fails. We demonstrate how our version of the GBP algorithm outperforms BP on synthetic and natural images and in both cases, GBP converges after on...
Ifeoma Nwogu, Jason J. Corso
Added 12 Oct 2009
Updated 28 Oct 2009
Type Conference
Year 2008
Where CVPR
Authors Ifeoma Nwogu, Jason J. Corso
Comments (0)
books