The University of Southampton
University of Southampton Institutional Repository

Robust 2D Ear Registration and Recognition Based on SIFT Point Matching

Bustard, John D. and Nixon, Mark (2008) Robust 2D Ear Registration and Recognition Based on SIFT Point Matching At BTAS 2008.

Record type: Conference or Workshop Item (Paper)

Abstract

Significant recent progress has shown ear recognition to be a viable biometric. Good recognition rates have been demonstrated under controlled conditions, using manual registration or with specialised equipment. This paper describes a new technique which improves the robustness of ear registration and recognition, addressing issues of pose variation, background clutter and occlusion. By treating the ear as a planar surface and creating a homography transform using SIFT feature matches, ears can be registered accurately. The feature matches reduce the gallery size and enable a precise ranking using a simple 2D distance algorithm. When applied to the XM2VTS database it gives results comparable to PCA with manual registration. Further analysis on more challenging datasets demonstrates the technique to be robust to background clutter, viewing angles up to ±13 degrees and with over 20% occlusion.

PDF Robust2DEarRegistrationAndRecognition.pdf - Version of Record
Download (687kB)

More information

Published date: 29 September 2008
Venue - Dates: BTAS 2008, 2008-09-29
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 266782
URI: http://eprints.soton.ac.uk/id/eprint/266782
PURE UUID: 1f65c3bb-cbea-4ab2-a202-550d23afa328

Catalogue record

Date deposited: 13 Oct 2008 10:20
Last modified: 18 Jul 2017 07:12

Export record

Contributors

Author: John D. Bustard
Author: Mark Nixon

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.

×