Simultaneous feature and dictionary learning for image set based face recognition

Jiwen Lu, Gang Wang, Weihong Deng, Pierre Moulin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a simultaneous feature and dictionary learning (SFDL) method for image set based face recognition, where each training and testing example contains a face image set captured from different poses, illuminations, expressions and resolutions. While several feature learning and dictionary learning methods have been proposed for image set based face recognition in recent years, most of them learn the features and dictionaries separately, which may not be powerful enough because some discriminative information for dictionary learning may be compromised in the feature learning stage if they are applied sequentially, and vice versa. To address this, we propose a SFDL method to learn discriminative features and dictionaries simultaneously from raw face images so that discriminative information can be jointly exploited. Extensive experimental results on four widely used face datasets show that our method achieves better performance than state-of-the-art image set based face recognition methods.

Original languageEnglish (US)
Title of host publicationComputer Vision, ECCV 2014 - 13th European Conference, Proceedings
PublisherSpringer-Verlag Berlin Heidelberg
Pages265-280
Number of pages16
EditionPART 1
ISBN (Print)9783319105895
DOIs
StatePublished - Jan 1 2014
Event13th European Conference on Computer Vision, ECCV 2014 - Zurich, Switzerland
Duration: Sep 6 2014Sep 12 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume8689 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th European Conference on Computer Vision, ECCV 2014
CountrySwitzerland
CityZurich
Period9/6/149/12/14

Keywords

  • Face recognition
  • dictionary learning
  • feature learning
  • image set
  • simultaneous learning

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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