In this paper, we propose an elegant approach for illumination invariant face recognition based on the photometric stereo technique. The basic idea is to reconstruct the surface normal and the albedo of a face using photometric stereo images, and then use them as the illumination independent model of the face. And, we have investigated the optimal light source directions for accurate surface shape reconstruction, and the robust estimation technique for the illumination direction of an input face image. We have tested the proposed algorithm with 125 real face images of 25 persons which are taken under 5 quite different illumination conditions, and achieved the success rate of more than 80%. Comparison results of conventional face recognition methods and the proposed method are also evaluated. These results demonstrate that the proposed technique have a great potential for the robust face recognition even when the lighting condition changes severely.
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Seok Cheol KEE, Kyoung Mu LEE, Sang Uk LEE, "Illumination Invariant Face Recognition Using Photometric Stereo" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 7, pp. 1466-1474, July 2000, doi: .
Abstract: In this paper, we propose an elegant approach for illumination invariant face recognition based on the photometric stereo technique. The basic idea is to reconstruct the surface normal and the albedo of a face using photometric stereo images, and then use them as the illumination independent model of the face. And, we have investigated the optimal light source directions for accurate surface shape reconstruction, and the robust estimation technique for the illumination direction of an input face image. We have tested the proposed algorithm with 125 real face images of 25 persons which are taken under 5 quite different illumination conditions, and achieved the success rate of more than 80%. Comparison results of conventional face recognition methods and the proposed method are also evaluated. These results demonstrate that the proposed technique have a great potential for the robust face recognition even when the lighting condition changes severely.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_7_1466/_p
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@ARTICLE{e83-d_7_1466,
author={Seok Cheol KEE, Kyoung Mu LEE, Sang Uk LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Illumination Invariant Face Recognition Using Photometric Stereo},
year={2000},
volume={E83-D},
number={7},
pages={1466-1474},
abstract={In this paper, we propose an elegant approach for illumination invariant face recognition based on the photometric stereo technique. The basic idea is to reconstruct the surface normal and the albedo of a face using photometric stereo images, and then use them as the illumination independent model of the face. And, we have investigated the optimal light source directions for accurate surface shape reconstruction, and the robust estimation technique for the illumination direction of an input face image. We have tested the proposed algorithm with 125 real face images of 25 persons which are taken under 5 quite different illumination conditions, and achieved the success rate of more than 80%. Comparison results of conventional face recognition methods and the proposed method are also evaluated. These results demonstrate that the proposed technique have a great potential for the robust face recognition even when the lighting condition changes severely.},
keywords={},
doi={},
ISSN={},
month={July},}
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TY - JOUR
TI - Illumination Invariant Face Recognition Using Photometric Stereo
T2 - IEICE TRANSACTIONS on Information
SP - 1466
EP - 1474
AU - Seok Cheol KEE
AU - Kyoung Mu LEE
AU - Sang Uk LEE
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2000
AB - In this paper, we propose an elegant approach for illumination invariant face recognition based on the photometric stereo technique. The basic idea is to reconstruct the surface normal and the albedo of a face using photometric stereo images, and then use them as the illumination independent model of the face. And, we have investigated the optimal light source directions for accurate surface shape reconstruction, and the robust estimation technique for the illumination direction of an input face image. We have tested the proposed algorithm with 125 real face images of 25 persons which are taken under 5 quite different illumination conditions, and achieved the success rate of more than 80%. Comparison results of conventional face recognition methods and the proposed method are also evaluated. These results demonstrate that the proposed technique have a great potential for the robust face recognition even when the lighting condition changes severely.
ER -