Imagination: Exploiting Link Analysis for Accurate Image Annotation

Abstract. The advent of digital photography calls for effective techniques for managing growing amounts of color images. Systems that only rely on low-level image features are nowadays limited by the semantic gap problem, which leads to a mismatch between the user subjective notion of similarity and the one adopted by a system. A possible way to reduce the semantic gap is to (semi-)automatically assign meaningful terms to images, so as to enable a high-level, concept-based, retrieval. In this paper we explore the opportunities offered by graph-based link analysis techniques in the development of a semi-automatic image captioning system. The approach we propose is appealing since the predicted terms for an image are in variable number, depending on the image content, t correlated terms, and can also describe abstract concepts. We present preliminary results on our prototype system and discuss possible extensions.

• Type: Conference
• Year: 2007
• Where: AMR
• Authors: Ilaria Bartolini, Paolo Ciaccia
• Keywords: AMR 2007, Low-level Image Features, Multimedia, Semantic Gap, Semantic Gap Problem