Recognizing landmarks using automated classification techniques: evaluation of various visual features (Contributo in atti di convegno)

Type

• Contributo in atti di convegno (Classe)
• Prodotto della ricerca (Classe)

Label

• Recognizing landmarks using automated classification techniques: evaluation of various visual features (Contributo in atti di convegno) (literal)

Anno

• 2010-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.1109/MMEDIA.2010.20 (literal)

Alternative label

• Amato G.; Falchi F.; Bolettieri P. (2010)
  Recognizing landmarks using automated classification techniques: evaluation of various visual features
  in 2010 Second International Conferences on Advances in Multimedia, Athens/Glyfada, Greece, 13-19 June 2010
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Amato G.; Falchi F.; Bolettieri P. (literal)

Pagina inizio

• 78 (literal)

Pagina fine

• 83 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

• http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5501609 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note

• In: MMEDIA 2010 - 2010 Second International Conferences on Advances in Multimedia (Athens/Glyfada, Greece, 13-19 June 2010). Proceedings, pp. 78 - 83. IEEE, 2010. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto

• ABSTRACT: In this paper, the performance of several visual features is evaluated in automatically recognizing landmarks (monuments, statues, buildings, etc.) in pictures. A number of landmarks were selected for the test. Pictures taken from a test set were classified automatically trying to guess which landmark they contained. We evaluated both global and local features. As expected, local features performed better given their capability of being less affected to visual variations and given that landmarks are mainly static objects that generally also maintain static local features. Between the local features, SIFT outperformed SURF and ColorSIFT. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• CNR-ISTI, Pisa (literal)

Titolo

• Recognizing landmarks using automated classification techniques: evaluation of various visual features (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn

• 978-1-4244-7277-2 (literal)

Abstract

• In this paper, the performance of several visual features is evaluated in automatically recognizing landmarks (monuments, statues, buildings, etc.) in pictures. A number of landmarks were selected for the test. Pictures taken from a test set were classified automatically trying to guess which landmark they contained. We evaluated both global and local features. As expected, local features performed better given their capability of being less affected to visual variations and given that landmarks are mainly static objects that generally also maintain static local features. Between the local features, SIFT outperformed SURF and ColorSIFT. (literal)

Prodotto di

• Digital Libraries (ICT.P08.010.002) (Modulo)
• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)

Autore CNR

• PAOLO BOLETTIERI (Persona)
• FABRIZIO FALCHI (Unità di personale interno)
• GIUSEPPE AMATO (Persona)

Insieme di parole chiave

• Parole chiave di "Recognizing landmarks using automated classification techniques: evaluation of various visual features" (Insieme di parole chiave)

Incoming links:

Autore CNR di

• GIUSEPPE AMATO (Persona)
• PAOLO BOLETTIERI (Persona)
• FABRIZIO FALCHI (Unità di personale interno)

Prodotto

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Digital Libraries (ICT.P08.010.002) (Modulo)

Insieme di parole chiave di

• Parole chiave di "Recognizing landmarks using automated classification techniques: evaluation of various visual features" (Insieme di parole chiave)