In the context of the Multimedia Commons initiative, we extracted and indexed deep features of about 100M images uploaded on Flickr between 2004 and 2014 and published under a Creative Commons commercial or noncommercial license. The extracted features and an online demo built using the MI-File approximated data structure are both publicly available. The online CBIR system demonstrates the effectiveness of the deep features and the efficiency of the indexing approach.

Indexing 100M images with deep features and MI-File

Amato G;Falchi F;Gennaro C;Rabitti F
2016

Abstract

In the context of the Multimedia Commons initiative, we extracted and indexed deep features of about 100M images uploaded on Flickr between 2004 and 2014 and published under a Creative Commons commercial or noncommercial license. The extracted features and an online demo built using the MI-File approximated data structure are both publicly available. The online CBIR system demonstrates the effectiveness of the deep features and the efficiency of the indexing approach.
2016
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Image retrieval
Similarity search
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/337476
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