Illumination normalization using self-lighting ratios for 3D2D face recognition

Xi Zhao, Shishir K. Shah, Ioannis A. Kakadiaris

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

18 Scopus citations

Abstract

3D2D face recognition is beginning to gain attention from the research community. It takes advantage of 3D facial geometry to normalize the head pose and registers it into a canonical 2D space. In this paper, we present a novel illumination normalization approach for 3D2D face recognition which does not require any training or prior knowledge on the type, number, and direction of the lighting sources. Estimated using an image-specific filtering technique in the frequency domain, a self-lighting ratio is employed to suppress illumination differences. Experimental results on the UHDB11 and FRGC databases indicate that the proposed approach improves the performance significantly for face images with large illumination variations.

Original languageEnglish (US)
Title of host publicationComputer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
PublisherSpringer-Verlag
Pages220-229
Number of pages10
EditionPART 2
ISBN (Print)9783642338670
DOIs
StatePublished - 2012
EventComputer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings - Florence, Italy
Duration: Oct 7 2012Oct 13 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7584 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceComputer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
Country/TerritoryItaly
CityFlorence
Period10/7/1210/13/12

Keywords

  • 3D2D face recognition
  • Lighting ratio
  • illumination suppression

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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