Face recognition with independent component based super-resolution

Erçil, Aytül and Sezer, Osman Gökhan and Altunbaşak, Yücel (2006) Face recognition with independent component based super-resolution. In: Visual Communications and Image Processing 2006, California

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Performance of current face recognition algorithms reduces significantly when they are applied to low-resolution face images. To handle this problem, super-resolution techniques can be applied either in the pixel domain or in the face subspace. Since face images are high dimensional data which are mostly redundant for the face recognition task, feature extraction methods that reduce the dimension of the data are becoming standard for face analysis. Hence, applying superresolution in this feature domain, in other words in face subspace, rather than in pixel domain, brings many advantages in computation together with robustness against noise and motion estimation errors. Therefore, we propose new superresolution algorithms using Bayesian estimation and projection onto convex sets methods in feature domain and present a comparative analysis of the proposed algorithms with those already in the literature.
Item Type: Papers in Conference Proceedings
Uncontrolled Keywords: Face recognition, super resolution, independent component analysis, projection onto convex sets, bayesian estimation.
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Aytül Erçil
Date Deposited: 20 Dec 2006 02:00
Last Modified: 26 Apr 2022 08:31
URI: https://research.sabanciuniv.edu/id/eprint/1163

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