University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Handling high dimensionality in biometric classification with multiple quality measures using locality preserving projection

Kryszczuk, K and Poh, N (2010) Handling high dimensionality in biometric classification with multiple quality measures using locality preserving projection In: CVPRW 2010, 2010-06-13 - 2010-06-18, San Francisco, USA.

Full text not available from this repository.

Abstract

The use of quality measures in biometrics is rapidly becoming the standard strategy for improving performance of biometric systems, especially in the presence of variable environmental conditions of signal capture. It is often necessary to integrate multiple quality measures into the classification process in order to capture the relevant aspects of signal quality. The inclusion of multiple quality features quickly increases the dimensionality of the classification problem, which leads to the risks of overfitting and dimensionality curse. So far, no mature strategy of coping with multiple quality measures has been developed. In this paper we propose to use a scheme, where the dimensionality of the vector of quality measures is reduced using the Locality Preserving Projections. We show that the proposed technique offers higher accuracy and better generalization properties than existing techniques of classification with quality measures, in same- and cross-device biometric matching scenarios.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
NameEmailORCID
Kryszczuk, KUNSPECIFIEDUNSPECIFIED
Poh, Nn.poh@surrey.ac.ukUNSPECIFIED
Date : 2010
Identification Number : https://doi.org/10.1109/CVPRW.2010.5544619
Contributors :
ContributionNameEmailORCID
publisherIEEE, UNSPECIFIEDUNSPECIFIED
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 11:54
Last Modified : 17 May 2017 14:59
URI: http://epubs.surrey.ac.uk/id/eprint/833181

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year


Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800