Similarity-Based Browsing of Image Search Results

Abstract

In this demo paper, we present an image browsing system that is suitable for online visualisation and browsing of search results from Google Images. Our approach is based on the Huffman tables available in the JPEG headers of Google Images thumbnails. Since these are adapted to the images, we employ them directly as image features. We then generate a visualisation of the search results by projection onto a 2-dimensional visualisation space based on principal component analysis derived from the Huffman entries. Images are dynamically placed into a grid structure and organised in a tree-like hierarchy for visual browsing. Since we utilise information only from the JPEG header, the requirements in terms of bandwidth are low, while no explicit feature calculation needs to be performed, thus allowing for interactive browsing of online image search results.