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Proceedings Paper

A fast approach for integrating ORB descriptors in the bag of words model
Author(s): Costantino Grana; Daniele Borghesani; Marco Manfredi; Rita Cucchiara
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Paper Abstract

In this paper we propose to integrate the recently introduces ORB descriptors in the currently favored approach for image classification, that is the Bag of Words model. In particular the problem to be solved is to provide a clustering method able to deal with the binary string nature of the ORB descriptors. We suggest to use a k-means like approach, called k-majority, substituting Euclidean distance with Hamming distance and majority selected vector as the new cluster center. Results combining this new approach with other features are provided over the ImageCLEF 2011 dataset.

Paper Details

Date Published: 7 March 2013
PDF: 8 pages
Proc. SPIE 8667, Multimedia Content and Mobile Devices, 866709 (7 March 2013); doi: 10.1117/12.2008460
Show Author Affiliations
Costantino Grana, Univ. degli Studi di Modena e Reggio Emilia (Italy)
Daniele Borghesani, Univ. degli Studi di Modena e Reggio Emilia (Italy)
Marco Manfredi, Univ. degli Studi di Modena e Reggio Emilia (Italy)
Rita Cucchiara, Univ. degli Studi di Modena e Reggio Emilia (Italy)

Published in SPIE Proceedings Vol. 8667:
Multimedia Content and Mobile Devices
Reiner Creutzburg; Todor G. Georgiev; Dietmar Wüller; Cees G. M. Snoek; Kevin J. Matherson; David Akopian; Andrew Lumsdaine; Lyndon S. Kennedy, Editor(s)

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