Bag of visual words revisited

Abstract

Visual information retrieval systems have gained importance due to the increasing amount of available digital multimedia data. Local features employing a bag of words approach from text retrieval have outperformed global features and have enhanced retrieval performance in large data sets. In this paper we conduct an exploratory study revisiting the bag of visual words approach for content based image retrieval. We apply a fuzzy clustering technique for visual words creation and visual words assignment and show in a first attempt that fuzzy clustering leads to more robust results in terms of retrieval performance.