Robust face recognition using 2D and 3D data: Pose and illumination compensation
The paper addresses the problem of face recognition under varying pose and illumination. Robustness to appearance variations is achieved not only by using a combination of a 2D color and a 3D image of the face, but mainly by using face geometry information to cope with pose and illumination variatio...
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Published in: | Pattern recognition Vol. 38; no. 12; pp. 2537 - 2548 |
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Main Authors: | , |
Format: | Journal Article |
Language: | English |
Published: |
Elsevier Ltd
01-12-2005
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Subjects: | |
Online Access: | Get full text |
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Summary: | The paper addresses the problem of face recognition under varying pose and illumination. Robustness to appearance variations is achieved not only by using a combination of a 2D color and a 3D image of the face, but mainly by using face geometry information to cope with pose and illumination variations that inhibit the performance of 2D face recognition. A face normalization approach is proposed, which unlike state-of-the-art techniques is computationally efficient and does not require an extended training set. Experimental results on a large data set show that template-based face recognition performance is significantly benefited from the application of the proposed normalization algorithms prior to classification. |
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ISSN: | 0031-3203 1873-5142 |
DOI: | 10.1016/j.patcog.2005.02.001 |