SVDD-Based illumination compensation for face recognition

Sang Woong Lee, Seong Whan Lee

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

2 Citations (Scopus)

Abstract

Illumination change is one of most important and difficult problems which prevent from applying face recognition to real applications. For solving this, we propose a method to compensate for different illumination conditions based on SVDD(Support Vector Data Description). In the proposed method, we first consider the SVDD training for the data belonging to the facial images under various illuminations, and model the data region for each illumination as the ball resulting from the SVDD training. Next, we compensate for illumination changes using feature vector projection onto the decision boundary of the SVDD ball. Finally, we obtain the pre-image under the identical illumination with input image. By repeated for each person, we can recognize a person with facial images under same illumination. We also perform the face recognition in order to verify the efficacy of proposed method.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages154-162
Number of pages9
Volume4642 LNCS
Publication statusPublished - 2007 Dec 1
Event2007 International Conference on Advances in Biometrics, ICB 2007 - Seoul, Korea, Republic of
Duration: 2007 Aug 272007 Aug 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4642 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2007 International Conference on Advances in Biometrics, ICB 2007
CountryKorea, Republic of
CitySeoul
Period07/8/2707/8/29

Keywords

  • Face recognition
  • Face reconstruction
  • Illumination compensation
  • Noise
  • Support vector data description

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Lee, S. W., & Lee, S. W. (2007). SVDD-Based illumination compensation for face recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4642 LNCS, pp. 154-162). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4642 LNCS).