Contributo in atti di convegno, 2010, ENG, 10.1109/MMEDIA.2010.20

Recognizing landmarks using automated classification techniques: evaluation of various visual features

Amato G.; Falchi F.; Bolettieri P.

CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy

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.

2010 Second International Conferences on Advances in Multimedia, pp. 78–83, Athens/Glyfada, Greece, 13-19 June 2010

Keywords

Content Analysis and Indexing, Information Search and Retrieval, Image indexing, Image classification, Recognition

CNR authors

Amato Giuseppe, Bolettieri Paolo, Falchi Fabrizio

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"