Istituto di Scienza e Tecnologie dell'Informazione     
Amato G., Bolettieri P., Falchi F., Gennaro C. Large scale image retrieval using vector of locally aggregated descriptors. In: SISAP 2013 - Similarity Search and Applications. 6th International Conference (A Coruņa, Spain, 2-4 October 2013). Proceedings, pp. 245 - 256. Nieves Brisaboa, Oscar Pedreira, Pavel Zezula. (Lecture Notes in Computer Science, vol. 8199). Springer, 2013.
Vector of locally aggregated descriptors (VLAD) is a promising approach for addressing the problem of image search on a very large scale. This representation is proposed to overcome the quantization error problem faced in Bag-of-Words (BoW) representation. However, text search engines have not be used yet for indexing VLAD given that it is not a sparse vector of occurrence counts. For this reason BoW approach is still the most widely adopted method for finding images that represent the same object or location given an image as a query and a large set of images as dataset. In this paper, we propose to enable inverted files of standard text search engines to exploit VLAD representation to deal with large-scale image search scenarios. We show that the use of inverted files with VLAD significantly outperforms BoW in terms of efficiency and effectiveness on the same hardware and software infrastructure.
URL: http://link.springer.com/chapter/10.1007%2F978-3-642-41062-8_25
DOI: 10.1007/978-3-642-41062-8_25
Subject Local feature
Computer vision
H.3.3 Information Search and Retrieval

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