Conceptual Query Expansion and Visual Search Results Exploration for Web Image Retrieval

摘要

Most approaches to image retrieval on the Web have their basis in document search techniques. Images are indexed based on the text that is related to the images. Queries are matched to this text to produce a set of search results, which are organized in paged grids that are reminiscent of lists of documents. Due to ambiguity both with the user-supplied query and with the text used to describe the images within the search index, most image searches contain many irrelevant images distributed throughout the search results. In this paper we present a method for addressing this problem. We perform conceptual query expansion using Wikipedia in order to generate a diverse range of images for each query, and then use a multi-resolution self organizing map to group visually similar images. The resulting interface acts as an intelligent search assistant, automatically diversifying the search results and then allowing the searcher to interactively highlight and filter images based on the concepts, and zoom into an area within the image space to show additional images that are visually similar.