Model-based reconstruction for illumination variation in face images

B.J. Boom; Lieuwe Jan Spreeuwers; Raymond N.J. Veldhuis

doi:10.1109/AFGR.2008.4813364

Model-based reconstruction for illumination variation in face images

B.J. Boom, Lieuwe Jan Spreeuwers, Raymond N.J. Veldhuis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

3 Citations (Scopus)

61 Downloads (Pure)

Abstract

We propose a novel method to correct for arbitrary illumination variation in the face images. The main purpose is to improve recognition results of face images taken under uncontrolled illumination conditions. We correct the illumination variation in the face images using a face shape model, which allows us to estimate the face shape in the face image. Using this face shape, we can reconstruct a face image under frontal illumination. These reconstructed images improve the results in face identification. We experimented both with face images acquired under different controlled illumination conditions in a laboratory and under uncontrolled illumination conditions.

Original language	Undefined
Title of host publication	8th IEEE International Conference on Automatic Face and Gesture Recognition
Place of Publication	Los Alamitos
Publisher	IEEE Computer Society Press
Pages	1-6
Number of pages	6
ISBN (Print)	978-1-4244-2154-1
DOIs	https://doi.org/10.1109/AFGR.2008.4813364
Publication status	Published - 19 Sep 2008
Event	8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008 - Amsterdam, Netherlands Duration: 17 Sep 2008 → 19 Sep 2008 Conference number: 8

Publication series

Name
Publisher	IEEE Computer Society Press

Conference

Conference	8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008
Abbreviated title	FG
Country	Netherlands
City	Amsterdam
Period	17/09/08 → 19/09/08

Keywords

EWI-13514
SCS-Safety
Face Recognition
IR-65006
Illumination Normalization
METIS-263690

Access to Document

10.1109/AFGR.2008.4813364

paper_illumination4
open
paper_illumination4
open

Cite this

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title = "Model-based reconstruction for illumination variation in face images",

abstract = "We propose a novel method to correct for arbitrary illumination variation in the face images. The main purpose is to improve recognition results of face images taken under uncontrolled illumination conditions. We correct the illumination variation in the face images using a face shape model, which allows us to estimate the face shape in the face image. Using this face shape, we can reconstruct a face image under frontal illumination. These reconstructed images improve the results in face identification. We experimented both with face images acquired under different controlled illumination conditions in a laboratory and under uncontrolled illumination conditions.",

keywords = "EWI-13514, SCS-Safety, Face Recognition, IR-65006, Illumination Normalization, METIS-263690",

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Boom, BJ, Spreeuwers, LJ & Veldhuis, RNJ 2008, Model-based reconstruction for illumination variation in face images. in 8th IEEE International Conference on Automatic Face and Gesture Recognition., 10.1109/AFGR.2008.4813364, IEEE Computer Society Press, Los Alamitos, pp. 1-6, 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008, Amsterdam, Netherlands, 17/09/08. https://doi.org/10.1109/AFGR.2008.4813364

Model-based reconstruction for illumination variation in face images. / Boom, B.J.; Spreeuwers, Lieuwe Jan ; Veldhuis, Raymond N.J.

8th IEEE International Conference on Automatic Face and Gesture Recognition. Los Alamitos : IEEE Computer Society Press, 2008. p. 1-6 10.1109/AFGR.2008.4813364.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AB - We propose a novel method to correct for arbitrary illumination variation in the face images. The main purpose is to improve recognition results of face images taken under uncontrolled illumination conditions. We correct the illumination variation in the face images using a face shape model, which allows us to estimate the face shape in the face image. Using this face shape, we can reconstruct a face image under frontal illumination. These reconstructed images improve the results in face identification. We experimented both with face images acquired under different controlled illumination conditions in a laboratory and under uncontrolled illumination conditions.

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