PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Amato G., Bolettieri P., Falchi F., Gennaro C., Rabitti F. Combining local and global visual feature similarity using a text search engine. In: CBMI 2011 - 9th International Workshop on Content-Based Multimedia Indexing (Madrid, 13-15 June 2011). Proceedings, pp. 49 - 54. IEEE, 2011.
 
 
Abstract
(English)
In this paper we propose a novel approach that allows processing image content based queries expressed as arbitrary combinations of local and global visual features, by using a single index realized as an inverted file. The index was implemented on top of the Lucene retrieval engine. This is particularly useful to allow people to efficiently and interactively check the quality of the retrieval result by exploiting combinations of features, by using a single index realized as an inverted file. The index was implemented on top of the Lucene retrieval engine. This is particularly useful to allow people to efficiently and interactively check the quality of the retrieval result by exploiting combinations of various features when using various features when using content based retrieval systems.
URL: http://dx.doi.org/10.1109/CBMI.2011.5972519
DOI: 10.1109/CBMI.2011.5972519
Subject CBIR
Indexing
Image
Transform coding
H.3.1 Content Analysis and Indexing
H.3.3 Information Search and Retrieval


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