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Authors: Giuseppe Amato ; Fabrizio Falchi and Claudio Gennaro

Affiliation: Institute of Information Science and Technologies and CNR, Italy

ISBN: 978-989-8565-47-1

Keyword(s): Bag of Features, Bag of Words, Local Features, Content based Image Retrieval, Landmark Recognition.

Abstract: A new class of applications based on visual search engines are emerging, especially on smart-phones that have evolved into powerful tools for processing images and videos. 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 this 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 and we study the effects of this reduction on effectiveness in landmark recognition and retrieval scenarios. We show that very relevant improvement in performance are achievable still preserving the advantage s of the BoF base approach. (More)

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Paper citation in several formats:
Amato G., Falchi F. and Gennaro C. (2013). On Reducing the Number of Visual Words in the Bag-of-Features Representation.In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 657-662. DOI: 10.5220/0004290506570662

@conference{visapp13,
author={Giuseppe Amato and Fabrizio Falchi and Claudio Gennaro},
title={On Reducing the Number of Visual Words in the Bag-of-Features Representation},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={657-662},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004290506570662},
isbn={978-989-8565-47-1},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - On Reducing the Number of Visual Words in the Bag-of-Features Representation
SN - 978-989-8565-47-1
AU - Amato G.
AU - Falchi F.
AU - Gennaro C.
PY - 2013
SP - 657
EP - 662
DO - 10.5220/0004290506570662

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