Robust face recognition across lighting variations using synthesized exemplars

Sang Woong Lee; Song Hyang Moon; Seong Whan Lee

doi:10.1007/11538059_23

Robust face recognition across lighting variations using synthesized exemplars

Sang Woong Lee, Song Hyang Moon, Seong Whan Lee

Department of Artificial Intelligence

Research output: Contribution to journal › Conference article › peer-review

Abstract

In this paper, we propose a new face recognition method under arbitrary lighting conditions, given only a single registered image and training data under unknown illuminations. Our proposed method is based on the exemplars which are synthesized from photometric stereo images of training data and the linear combination of those exemplars are used to represent the new face. We make experiments for verifying our approach and compare it with two traditional approaches. As a result, higher recognition rates are reported in these experiments using the illumination subset of Max-Planck Institute Face Database.

Original language	English
Pages (from-to)	213-222
Number of pages	10
Journal	Lecture Notes in Computer Science
Volume	3644
Issue number	PART I
DOIs	https://doi.org/10.1007/11538059_23
Publication status	Published - 2005
Event	International Conference on Intelligent Computing, ICIC 2005 - Hefei, China Duration: 2005 Aug 23 → 2005 Aug 26

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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10.1007/11538059_23

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title = "Robust face recognition across lighting variations using synthesized exemplars",

abstract = "In this paper, we propose a new face recognition method under arbitrary lighting conditions, given only a single registered image and training data under unknown illuminations. Our proposed method is based on the exemplars which are synthesized from photometric stereo images of training data and the linear combination of those exemplars are used to represent the new face. We make experiments for verifying our approach and compare it with two traditional approaches. As a result, higher recognition rates are reported in these experiments using the illumination subset of Max-Planck Institute Face Database.",

author = "Lee, {Sang Woong} and Moon, {Song Hyang} and Lee, {Seong Whan}",

note = "Funding Information: This research was supported by the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Commerce, Industry and Energy of Korea and we would like to thank the Max-Planck-Institute for providing the MPI Face Database.; International Conference on Intelligent Computing, ICIC 2005 ; Conference date: 23-08-2005 Through 26-08-2005",

year = "2005",

doi = "10.1007/11538059_23",

language = "English",

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journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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T1 - Robust face recognition across lighting variations using synthesized exemplars

AU - Lee, Sang Woong

AU - Moon, Song Hyang

AU - Lee, Seong Whan

N1 - Funding Information: This research was supported by the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Commerce, Industry and Energy of Korea and we would like to thank the Max-Planck-Institute for providing the MPI Face Database.

PY - 2005

Y1 - 2005

N2 - In this paper, we propose a new face recognition method under arbitrary lighting conditions, given only a single registered image and training data under unknown illuminations. Our proposed method is based on the exemplars which are synthesized from photometric stereo images of training data and the linear combination of those exemplars are used to represent the new face. We make experiments for verifying our approach and compare it with two traditional approaches. As a result, higher recognition rates are reported in these experiments using the illumination subset of Max-Planck Institute Face Database.

AB - In this paper, we propose a new face recognition method under arbitrary lighting conditions, given only a single registered image and training data under unknown illuminations. Our proposed method is based on the exemplars which are synthesized from photometric stereo images of training data and the linear combination of those exemplars are used to represent the new face. We make experiments for verifying our approach and compare it with two traditional approaches. As a result, higher recognition rates are reported in these experiments using the illumination subset of Max-Planck Institute Face Database.

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U2 - 10.1007/11538059_23

DO - 10.1007/11538059_23

M3 - Conference article

AN - SCOPUS:27144436811

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EP - 222

JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

IS - PART I

T2 - International Conference on Intelligent Computing, ICIC 2005

Y2 - 23 August 2005 through 26 August 2005

ER -

Robust face recognition across lighting variations using synthesized exemplars

Abstract

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