Multimodal face recognition: Combination of geometry with physiological information

I. A. Kakadiaris, G. Passalis, T. Theoharis, G. Toderici, I. Konstantinidis, N. Murtuza

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

42 Scopus citations

Abstract

It is becoming increasingly important to be able to credential and identify authorized personnel at key points of entry. Such identity management systems commonly employ biometric identifiers. In this paper, we present a novel multimodal facial recognition approach that employs data from both visible spectrum and thermal infrared sensors. Data from multiple cameras is used to construct a three-dimensional mesh representing the face and a facial thermal texture map. An annotated face model with explicit two-dimensional parameterization (UV) is then filled to this data to construct: 1) a three-channel UV deformation image encoding geometry, and 2) a one-channel UV vasculature image encoding facial vasculature. Recognition is accomplished by comparing: 1) the parametric deformation images, 2) the parametric vasculature images, and 3) the visible spectrum texture maps. The novelty of our work lies in the use of deformation images and physiological information as means for comparison. We have performed extensive tests on the Face Recognition Grand Challenge v1.0 dataset and on our own multimodal database with very encouraging results.

Original languageEnglish (US)
Title of host publicationProceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1022-1029
Number of pages8
ISBN (Print)0769523722, 9780769523729
DOIs
StatePublished - 2005
Event2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - San Diego, CA, United States
Duration: Jun 20 2005Jun 25 2005

Publication series

NameProceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
VolumeII

Other

Other2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
Country/TerritoryUnited States
CitySan Diego, CA
Period6/20/056/25/05

ASJC Scopus subject areas

  • General Engineering

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