An ensemble approach to robust biometrics fusion

Costin Barbu, Raja Iqbal, Jing Peng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A clever information fusion algorithm is a key component in designing a robust multimodal biometrics algorithm. We present a novel information fusion approach that can be a very useful tool for multimodal biometrics learning. The proposed technique is a multiple view generalization of AdaBoost in the sense that weak learners from various information sources are selected in each iteration based on lowest weighted error rate. Weak learners trained on individual views in each iteration rectify the bias introduced by learners in preceding iterations resulting in a self regularizing behavior. We compare the classification performance of proposed technique with recent classifier fusion strategies in various domains such as face detection, gender classification and texture classification.

Original languageEnglish
Title of host publication2006 Conference on Computer Vision and Pattern Recognition Workshop
DOIs
StatePublished - 21 Dec 2006
Event2006 Conference on Computer Vision and Pattern Recognition Workshops - New York, NY, United States
Duration: 17 Jun 200622 Jun 2006

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2006
ISSN (Print)1063-6919

Other

Other2006 Conference on Computer Vision and Pattern Recognition Workshops
CountryUnited States
CityNew York, NY
Period17/06/0622/06/06

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