Context Analysis Using a Bayesian Normal Graph

Contextual information can be used to help object detection in video and images, or to categorize text. In this work we demonstrate how the Latent Variable Model, expressed as a Factor Graph in Reduced Normal Form, can manage contextual information to support a scene understanding task. In an unsupervised scenario our model learns how various objects can coexist, by associating object variables to a latent Bayesian cluster. The model, that is implemented using probabilistic message propagation, can be used to correct or to assign labels to new images.