Improving face classification with multiple-clustering induced feature reduction

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (Nid-Cyfnodolyn fathau)

1 Dyfyniadau(SciVal)

Crynodeb

For modern-age security, many have turn to biometrics such as face classification to verify authority. Despite this, the accuracy of existing classifiers have been constrained by the curse of dimensionality typically observed in face images. In order to simplify the task, one may ruduce the original data to a more compact variation, where only key feature components are included in the classification process. Unlike conventional feature reduction techniques found in the literature, this paper presents a novel method that makes use of cluster ensemble, specifically the summarizing information matrix, as the transformed data for a supervised learning step. Among different state-of-the-art methods, link-based cluster ensemble approach (LCE) provides a highly accurate clustering, and thus particularly employed here. The performance of this transformation model is evaluated on published face dataset and its noise-added variations, using different classifers. The findings suggest that the new model can improve the classification accuracy beyond those of other benchmark methods investigated in this empirical study.

Iaith wreiddiolSaesneg
TeitlICCST 2015 - The 49th Annual IEEE International Carnahan Conference on Security Technology
CyhoeddwrIEEE Press
Tudalennau241-246
Nifer y tudalennau6
ISBN (Electronig)9781479986910
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 21 Ion 2016
Digwyddiad49th Annual IEEE International Carnahan Conference on Security Technology, ICCST 2015 - Taipei, Taiwan
Hyd: 21 Medi 201524 Medi 2015

Cyfres gyhoeddiadau

EnwProceedings - International Carnahan Conference on Security Technology
Cyfrol2015-January
ISSN (Argraffiad)1071-6572

Cynhadledd

Cynhadledd49th Annual IEEE International Carnahan Conference on Security Technology, ICCST 2015
Gwlad/TiriogaethTaiwan
DinasTaipei
Cyfnod21 Medi 201524 Medi 2015

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