A hierarchical statistical model for object classification

In many applications it is necessary to be able to classify images in a database accurately and with acceptable speed. The main problem is to assign different images to right categories. The later problem becomes more challenging while dealing with large databases with many categories and subcategories. In this paper we propose a novel classification method based on an adopted hierarchical Dirichlet generative model, previously proposed for corpora document classification. In order to adopt the model to work with image data we use the bag of visual words model. We show that if properly applied the model can achieve adequate results for hierarchical image classification. Experimental results are presented and discussed to show the merits of the proposed approach.