The University of Southampton
University of Southampton Institutional Repository

Efficient clustering and quantisation of SIFT features: Exploiting characteristics of the SIFT descriptor and interest region detectors under image inversion

Hare, Jonathon, Samangooei, Sina and Lewis, Paul (2011) Efficient clustering and quantisation of SIFT features: Exploiting characteristics of the SIFT descriptor and interest region detectors under image inversion At The ACM International Conference on Multimedia Retrieval (ICMR 2011), Italy. 17 - 20 Apr 2011.

Record type: Conference or Workshop Item (Poster)

Abstract

The SIFT keypoint descriptor is a powerful approach to encoding local image description using edge orientation histograms. Through codebook construction via k-means clustering and quantisation of SIFT features we can achieve image retrieval treating images as bags-of-words. Intensity inversion of images results in distinct SIFT features for a single local image patch across the two images. Intensity in- versions notwithstanding these two patches are structurally identical. Through careful reordering of the SIFT feature vectors, we can construct the SIFT feature that would have been generated from a non-inverted image patch starting with those extracted from an inverted image patch. Fur- thermore, through examination of the local feature detection stage, we can estimate whether a given SIFT feature belongs in the space of inverted features, or non-inverted features. Therefore we can consistently separate the space of SIFT features into two distinct subspaces. With this knowledge, we can demonstrate reduced time complexity of codebook construction via clustering by up to a factor of four and also reduce the memory consumption of the clustering algorithms while producing equivalent retrieval results.

PDF Paper_17.pdf - Version of Record
Download (926kB)

More information

Published date: 17 April 2011
Additional Information: Event Dates: 17-20 April 2011
Venue - Dates: The ACM International Conference on Multimedia Retrieval (ICMR 2011), Italy, 2011-04-17 - 2011-04-20
Keywords: sift, image retrieval, clustering, bag of words
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 272237
URI: http://eprints.soton.ac.uk/id/eprint/272237
PURE UUID: dc6310e3-08b5-4f90-acf4-e4a0e1567b1b
ORCID for Jonathon Hare: ORCID iD orcid.org/0000-0003-2921-4283

Catalogue record

Date deposited: 30 Apr 2011 09:08
Last modified: 18 Jul 2017 06:33

Export record

Contributors

Author: Jonathon Hare ORCID iD
Author: Sina Samangooei
Author: Paul Lewis

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×