A fast approach for integrating ORB descriptors in the bag of words model

7 March 2013 A fast approach for integrating ORB descriptors in the bag of words model

Costantino Grana, Daniele Borghesani, Marco Manfredi, Rita Cucchiara

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Proceedings Volume 8667, Multimedia Content and Mobile Devices; 866709 (2013) https://doi.org/10.1117/12.2008460
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

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.

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Costantino Grana, Daniele Borghesani, Marco Manfredi, and Rita Cucchiara "A fast approach for integrating ORB descriptors in the bag of words model", Proc. SPIE 8667, Multimedia Content and Mobile Devices, 866709 (7 March 2013); https://doi.org/10.1117/12.2008460

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