Imagination: Exploiting Link Analysis for Accurate Image Annotation

13 years 10 months ago

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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.

Ilaria Bartolini, Paolo Ciaccia

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