Generalized Bayesian inference in a fuzzy context: From theory to a virtual reality application

A generalized Bayesian inference framework in order to embed fuzzy sets and partial probabilistic information is provided. The general framework of reference is that of coherent conditional probabilities, which allows giving a rigorous interpretation of membership function as a conditional probability, regarded as a function of the conditioning event. The inferential problem needs to be studied in situations where the prior can be partial: moreover, membership and prior can be given on different classes of events. This inferential model is applied for the virtual representation of a female avatar. (C) 2011 Elsevier B.V. All rights reserved.