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Automatic Face Annotation in News Images

pubblicato 24 mag 2011, 02:55 da Alberto Bartoli   [ aggiornato in data 24 mag 2011, 02:58 ]

E. Medvet, A. Bartoli, G. Davanzo, A. De Lorenzo,  
in Proc. 10-th IEEE / WIC / ACM International Conference on Web Intelligence
to appear.

We consider the automatic annotation of faces of people mentioned in news. News stories provide a constant flow of potentially useful image indexing information, due to their huge diffusion on the web and to the involvement of human operators in selecting relevant images for the stories. In this work we investigate the possibility of actually exploiting this wealth of information.

We propose and evaluate a system for automatic face annotation of image news that is fully unsupervised and does not require any prior knowledge about topic or people involved. Key feature of our proposal is that it attempts to identify the essential piece of information---how a person with a given name looks like---by querying popular image search engines. Mining the web allows overcoming intrinsic limitations of approaches built above a predefined collection of stories: our system can potentially annotate people never handled before since its knowledge base is constantly expanded, as long as search engines keep on indexing the web. On the other hand, leveraging on image search engines forces to cope with the substantial amount of noise in search engine results. Our contribution shows experimentally that automatic face annotation may indeed be achieved based entirely on knowledge that lives in the web.

IEEE/WIC/ACM WI-2011 is a highly selective conference; only 20,5% of the 200 submissions were accepted as regular papers and 19% of the 200 submissions were accepted as short papers. Papers went through a rigorous review process. Each paper was reviewed by at least three program committee members.