Traditional multimedia classification techniques are based on the analysis of either low-level features or annotated textual information. Instead, the semantic gap between rough data and its content is still a challenging task. In this paper, we describe a novel solution which automatically associates the image analysis and processing algorithms to keywords and human annotation. We use the well known Flickr system, that contains images, tags, keywords and sometimes useful annotation describing both the content of an image and personal interesting information describing the scene. We have carried out several experiments demonstrating that the proposed categorization process achieves quite good performances in terms of efficiency and effectiveness. © 2009 IEEE.

A system for automatic image categorization

Persia F.;
2009

Abstract

Traditional multimedia classification techniques are based on the analysis of either low-level features or annotated textual information. Instead, the semantic gap between rough data and its content is still a challenging task. In this paper, we describe a novel solution which automatically associates the image analysis and processing algorithms to keywords and human annotation. We use the well known Flickr system, that contains images, tags, keywords and sometimes useful annotation describing both the content of an image and personal interesting information describing the scene. We have carried out several experiments demonstrating that the proposed categorization process achieves quite good performances in terms of efficiency and effectiveness. © 2009 IEEE.
978-1-4244-4962-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/166107
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