Abstract

In this technical demonstration, we showcase the SBIA system – a search-based image annotation system. At the heart of the system lies a very large-scale image search engine which indexed three million Web images and supports both text and visual queries. Given an image (with initial annotations), SBIA first finds semantically/visually similar images via the search engine, and then mines representative keywords from the retrieved images. These keywords, after annotation rejection and relevance ranking, are finally used to annotate the query image.