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Binarized Eigenphases for Limited Memory Face Recognition Applications

Zaeri, Naser G. ; Mokhtarian, Farzin ; Cherri, Abdallah

The 5th International Conference on Computer Vision Systems, 2007
Bielefeld, 21. - 24. März 2007

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Abstract:
Most of the algorithms proposed for face recognition involve considerable amount of calculations, and hence they can not be used on devices of limited memory constraints. In this paper, we propose a novel solution for efficient face recognition problem for the systems that utilize low memory devices. The new technique applies the principal component analysis to the binarized phase spectrum of the Fourier transform of the covariance matrix constructed from the MPEG-7 Fourier Feature Descriptor vectors of the images. The binarization step that is applied to the phases adds many interesting advantages to the system. It will be shown that the proposed technique maximizes the recognition rate while achieving substantial savings in computational time, when compared to other known systems.


Keywords: Face recognition, limited memory, PCA, MPEG-7
Institution: Faculty of Technology, Research Groups in Informatics
DDC classification: Data processing, computer science, computer systems

Suggested Citation:
Zaeri, Naser G. ; Mokhtarian, Farzin ; Cherri, Abdallah  (2007)  Binarized Eigenphases for Limited Memory Face Recognition Applications. The 5th International Conference on Computer Vision Systems, 2007


URL: http://biecoll.ub.uni-bielefeld.de/volltexte/2007/14



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