A Bilinear Illumination Model for Robust Face Recognition

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A Bilinear Illumination Model for Robust Face Recognition

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Title: A Bilinear Illumination Model for Robust Face Recognition
Author: Lee, Jinho; Moghaddam, Baback; Pfister, Hanspeter; Machiraju, Raghu

Note: Order does not necessarily reflect citation order of authors.

Citation: Lee, Jinho, Baback Moghaddam, Hanspeter Pfister, and Raghu Machiraju. 2005. A bilinear illumination model for robust face recognition. Proceedings of the Tenth IEEE International Conference on Computer Vision: October 17-21, 2005, Beijing, China. 1177-1184. Los Almamitos, C.A.: IEEE Computer Society.
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Abstract: We present a technique to generate an illumination subspace for arbitrary 3D faces based on the statistics of measured illuminations under variable lighting conditions from many subjects. A bilinear model based on the higher-order singular value decomposition is used to create a compact illumination subspace given arbitrary shape parameters from a parametric 3D face model. Using a fitting procedure based on minimizing the distance of the input image to the dynamically changing illumination subspace, we reconstruct a shape-specific illumination subspace from a single photograph. We use the reconstructed illumination subspace in various face recognition experiments with variable lighting conditions and obtain accuracies which are very competitive with previous methods that require specific training sessions or multiple images of the subject.
Published Version: doi:10.1109/ICCV.2005.5
Other Sources: http://gvi.seas.harvard.edu/sites/all/files/iccv05_0.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4238979
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