In this paper we report on MICC participation to the Scalable Concept Image Annotation subtask of the ImageCLEF Photo An- notation and Retrieval competition. Our goal has been to investigate the applicability of data-driven methods that have obtained good results in the field of social image annotation and retrieval to web images. These methods have been applied typically to tasks such as tag ranking, tag suggestion and refinement. Since they do not require a training stage they can be applied in cases in which the set of annotation keywords can vary greatly over time or when the set of images to be analyzed is very large.
MICC-UNIFI at ImageCLEF 2013 Scalable Concept Image Annotation / Tiberio Uricchio; Marco Bertini; Lamberto Ballan; Alberto Del Bimbo. - ELETTRONICO. - (2013), pp. ---. (Intervento presentato al convegno CLEF 2013 Conference and Labs of the Evaluation Forum, ImageCLEF Track tenutosi a Valencia, Spain nel September).
MICC-UNIFI at ImageCLEF 2013 Scalable Concept Image Annotation
URICCHIO, TIBERIO;BERTINI, MARCO;BALLAN, LAMBERTO;DEL BIMBO, ALBERTO
2013
Abstract
In this paper we report on MICC participation to the Scalable Concept Image Annotation subtask of the ImageCLEF Photo An- notation and Retrieval competition. Our goal has been to investigate the applicability of data-driven methods that have obtained good results in the field of social image annotation and retrieval to web images. These methods have been applied typically to tasks such as tag ranking, tag suggestion and refinement. Since they do not require a training stage they can be applied in cases in which the set of annotation keywords can vary greatly over time or when the set of images to be analyzed is very large.
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