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Bidirectional relighting for 3D-aided 2D face recognition

Toderici, George; Passalis, Georgios; Zafeiriou, Stefanos; Tzimiropoulos, Georgios; Petrou, Maria; Theoharis, Theoharis; Kakadiaris, Ioannis A.


George Toderici

Georgios Passalis

Stefanos Zafeiriou

Georgios Tzimiropoulos

Maria Petrou

Theoharis Theoharis

Ioannis A. Kakadiaris


In this paper, we present a new method for bidirectional relighting for 3D-aided 2D face recognition under large pose and illumination changes. During subject enrollment, we build subject-specific 3D annotated models by using the subjects' raw 3D data and 2D texture. During authentication, the probe 2D images are projected onto a normalized image space using the subject-specific 3D model in the gallery. Then, a bidirectional relighting algorithm and two similarity metrics (a view-dependent complex wavelet structural similarity and a global similarity) are employed to compare the gallery and probe. We tested our algorithms on the UHDB11 and UHDB12 databases that contain 3D data with probe images under large lighting and pose variations. The experimental results show the robustness of our approach in recognizing faces in difficult situations.


Toderici, G., Passalis, G., Zafeiriou, S., Tzimiropoulos, G., Petrou, M., Theoharis, T., & Kakadiaris, I. A. (2010). Bidirectional relighting for 3D-aided 2D face recognition.

Conference Name IEEE Computer Society Conference on Computer Vision and Pattern Recognition
End Date Jun 18, 2010
Publication Date Jan 1, 2010
Deposit Date Jan 29, 2016
Publicly Available Date Jan 29, 2016
Peer Reviewed Peer Reviewed
Keywords Face Recognition, Image Texture, Wavelet Transforms
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Additional Information Published in: Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on: date, 13-18 June 2010. Piscataway, N.J. : IEEE, 2010, ISBN: 978-1-4244-6984-0. pp. 2721-2728, doi: 10.1109/CVPR.2010.5539995
©2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.


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