Finding Iconic Images

Abstract

We demonstrate that is it possible to automatically find representative example images of a specified object category. These canonical examples are perhaps the kind of images that one would show a child to teach them what, for example a horse is - images with a large object clearly separated from the background. Given a large collection of images returned by a web search for an object category, our approach proceeds without any user supplied training data for the category. First images are ranked according to a category independent composition model that predicts whether they contain a large clearly depicted object, and outputs an estimated location of that object. Then local features calculated on the proposed object regions are used to eliminate images not distinctive to the category and to cluster images by similarity of object appearance. We present results and a user evaluation on a variety of object categories, demonstrating the effectiveness of the approach.