Similarity Searches in Face Databases View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2009

AUTHORS

Annalisa Franco , Dario Maio

ABSTRACT

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. More... »

PAGES

443-450

Book

TITLE

Image Analysis and Processing – ICIAP 2009

ISBN

978-3-642-04145-7
978-3-642-04146-4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-04146-4_48

DOI

http://dx.doi.org/10.1007/978-3-642-04146-4_48

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1015214281


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