A Classification Based Framework For Concept Summarization

In this paper we propose a novel classification based framework for finding a small number of images summarizing a concept. Our method exploits metadata information available with the images to get the category information using Latent Dirichlet Allocation. We modify the import vector machine formulation based on kernel logistic regression to solve the underlying classification problem. We show that the import vectors provide a good summary satisfying important properties such as coverage, diversity and balance. Furthermore, the framework allows users to specify desired distribution