Scene exploration using Bayesian nets

Exploring scenes using Bayesian nets is based on the idea of performing an active knowledge based search on images unlike conventional visual recognition algorithms. During the active search of images, a sample set of training images from different classes is available right at the onset of an experiment and the nature of the class to be searched is unknown. Usually a recursive search on the images for objects, belonging to all classes is performed using a conventional object recognition system and our approach presented in the present paper can obviate this. The search by Bayesian nets can be confined only to a specific class or a set of classes, provided the relationships between constituent objects are exactly defined. We prove that if structural relationships are rightly established between the constituent objects of an image, searching scenes using Bayesian nets is quite effective and the presented results proclaim this very fact.