PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Amato G., Falchi F., Gennaro C. Visual features selection. In: IIR 2013 - Fourth Italian Information Retrieval Workshop (Pisa, 16-17 January 2013). Proceedings, vol. 964 pp. 41 - 44. Roberto Basili, Fabrizio Sebastiani, Giovanni Semeraro (eds.). (CEUR Workshop Proceedings, vol. 964). CEUR-WS.org, 2013.
 
 
Abstract
(English)
The state-of-the-art algorithms for large visual content recognition and content based similarity search today use the Bag of Features" (BoF) or Bag of Words (BoW) approach. The idea, borrowed from text retrieval, enables the use of inverted files. A very well known issue with the BoF approach is that the query images, as well as the stored data, are described with thousands of words. This poses obvious efficiency problems when using inverted files to perform efficient image matching. In this paper, we propose and compare various techniques to reduce the number of words describing an image to improve efficiency.
URL: http://ceur-ws.org/Vol-964/paper7.pdf
Subject Bag of features
Bag of words
Local features
Landmark recognition
H.3.3 Information Search and Retrieval


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