Mixed States Markov Random Fields with Symbolic Labels and Multidimensional Real Values

dc.creatorCernuschi-Frias, Bruno
dc.date2007-07-26
dc.date2007-07-30
dc.date.accessioned2026-07-07T13:04:29Z
dc.date.available2026-07-07T13:04:29Z
dc.descriptionNew theoretical results are presented here on the recently introduced model called mixed states MRF. Such models were introduced in the context of image motion analysis and are useful to represent information which can take both discrete values accounting for symbolic states, and real values corresponding to continuous measurements. In particular, results are given when the global energy for the Gibbs formulation expressing the mixed states model, can be decomposed into one term accounting for the discrete part of the model, and a second term related to the continuous part. This decomposition theorem permits to define conditional mixed states models in a very simple way.
dc.identifierhttps://arxiv.org/abs/0707.3986
dc.identifierhttp://arxiv.org/abs/0707.3986
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/227181
dc.subjectProbability
dc.titleMixed States Markov Random Fields with Symbolic Labels and Multidimensional Real Values
dc.typetext

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