Linear projection methods in face recognition under unconstrained illuminations: A comparative study

Qi Li, Jieping Ye, Chandra Kambhamettu

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

14 Citations (Scopus)

Abstract

Face recognition under unconstrained illuminations (FR/I) received extensive study because of the existence of illumination subspace. [2] presented a study on the comparison between Principal component analysis (PCA) and subspace Linear Discriminant Analysis (LDA) for this problem. PCA and subspace LDA are two well-known linear projection methods that can be characterized as trace optimization on scatter matrices. Generally, a linear projection method can be derived by applying a specific matrix analysis technique on specific scatter matrices under some optimization criterion. Several novel linear projection methods were proposed recently using Generalized Singular Value Decomposition or QR Decomposition matrix analysis techniques [10, 17, 11]. In this paper, we present a comparative study on these linear projection methods in FR/I. We further involve multiresolution analysis in the study. Our comparative study is expected to give a relatively comprehensive view on the performance of linear projection methods in FR/I problems.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2
StatePublished - 2004
Externally publishedYes
EventProceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004 - Washington, DC, United States
Duration: Jun 27 2004Jul 2 2004

Other

OtherProceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004
CountryUnited States
CityWashington, DC
Period6/27/047/2/04

Fingerprint

Face recognition
Lighting
Discriminant analysis
Principal component analysis
Multiresolution analysis
Singular value decomposition

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Software
  • Control and Systems Engineering

Cite this

Li, Q., Ye, J., & Kambhamettu, C. (2004). Linear projection methods in face recognition under unconstrained illuminations: A comparative study. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Vol. 2)

Linear projection methods in face recognition under unconstrained illuminations : A comparative study. / Li, Qi; Ye, Jieping; Kambhamettu, Chandra.

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2 2004.

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

Li, Q, Ye, J & Kambhamettu, C 2004, Linear projection methods in face recognition under unconstrained illuminations: A comparative study. in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. vol. 2, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004, Washington, DC, United States, 6/27/04.
Li Q, Ye J, Kambhamettu C. Linear projection methods in face recognition under unconstrained illuminations: A comparative study. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2. 2004
Li, Qi ; Ye, Jieping ; Kambhamettu, Chandra. / Linear projection methods in face recognition under unconstrained illuminations : A comparative study. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Vol. 2 2004.
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