2009 | OriginalPaper | Buchkapitel
Similarity Searches in Face Databases
verfasst von : Annalisa Franco, Dario Maio
Erschienen in: Image Analysis and Processing – ICIAP 2009
Verlag: Springer Berlin Heidelberg
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In this paper the problem of similarity searches in face databases is addressed. An approach based on relevance feedback is proposed to iteratively improve the query result. The approach is suitable both to supervised and unsupervised contexts. The efficacy of the learning procedures are confirmed by the results obtained on publicly available databases of faces.