Gabor feature selection for face recognition using improved AdaBoost learning

Linlin Shen, Li Bai, Daniel Bardsley, Yangsheng Wang

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

24 Citations (Scopus)

Abstract

Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual information into AdaBoost, we propose an improved boosting algorithm in this paper. The proposed method fully examines the redundancy between candidate classifiers and selected classifiers. The classifiers thus selected are both accurate and non-redundant. Experimental results show that the strong classifier learned using the proposed algorithm achieves a lower training error rate than AdaBoost. The proposed algorithm has also been applied to select discriminative Gabor features for face recognition. Even with the simple correlation distance measure and 1-NN classifier, the selected Gabor features achieve quite high recognition accuracy on the FERET database, where both expression and illumination variance exists. When only 140 features are used, the selected features achieve as high as 95.5% accuracy, which is about 2.5% higher than that of features selected by AdaBoost.

Original languageEnglish
Title of host publicationAdvances in Biometric Person Authentication - International Wokshop on Biometric Recognition Systems, IWBRS 2005, Proceedings
Pages39-49
Number of pages11
DOIs
Publication statusPublished - 2005
Externally publishedYes
EventInternational Wokshop on Biometric Recognition Systems, IWBRS 2005: Advances in Biometric Person Authentication - Beijing, China
Duration: 22 Oct 200523 Oct 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3781 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Wokshop on Biometric Recognition Systems, IWBRS 2005: Advances in Biometric Person Authentication
Country/TerritoryChina
CityBeijing
Period22/10/0523/10/05

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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