Illumination compensation and enhancement for face recognition

Muwei Jian, Kin Man Lam, Junyu Dong

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Face images of the same person under different illuminations represent a challenge for face recognition. Traditional methods based on the Lambertian model construct a face image invariant to illuminations by combining a number of the images of different illuminations linearly. A drawback with the Lambertian model is that a single-point light source placed at infinity is assumed. This paper proposes an efficient scheme for illumination compensation and enhancement of face images. Our illumination model is universal without requiring the assumption of a single-point light source, so it circumvents and overcomes the limitations of the Lambertian model. In practice, it is reasonable to assume that the variations in intensity and illumination directions cause the face images of the same person different. The proposed approach can learn the average representations of face images under changing illuminations so as to compensate or enhance the face images and to eliminate the effect of different and uneven illuminations while keeping the intrinsic properties of the face surface. Our experiments have provided promising results, demonstrating that the proposed methods are effective.
Original languageEnglish
Title of host publicationAPSIPA ASC 2011 - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011
Pages26-34
Number of pages9
Publication statusPublished - 1 Dec 2011
EventAsia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011 - Xi'an, China
Duration: 18 Oct 201121 Oct 2011

Conference

ConferenceAsia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011
Country/TerritoryChina
CityXi'an
Period18/10/1121/10/11

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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