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Preserving spatial information and overcoming variations in appearance for face recognition

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Abstract

Local feature-based approaches mainly aim to achieve robustness to variations in facial images by assuming that only some parts of the facial images may be affected. However, such approaches may lose spatial information. In this study, a compromise feature extraction scheme is studied which extracts local features while preserving spatial information. The proposed scheme exploits an ensemble of classifiers where each member is constructed using randomly selected design parameters including the size, number and location of sub-images for local feature extraction. Experiments conducted on FERET and ORL databases have shown that proposed scheme surpasses the local feature-based reference systems which focus on either local information or preserving spatial information.

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Acknowledgments

This work is supported by the research grant MEKB-07-06 provided by the Ministry of Education and Culture of Northern Cyprus. We would also like to thank to our colleagues Hüseyin Sertbay and Cem Ergün for their contributions in preprocessing image databases.

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Authors and Affiliations

  1. Department of Computer Engineering, Eastern Mediterranean University, Mağusa, Northern Cyprus, Turkey

    Önsen Toygar & Hakan Altınçay

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  1. Önsen Toygar
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  2. Hakan Altınçay
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Correspondence to Önsen Toygar.

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Toygar, Ö., Altınçay, H. Preserving spatial information and overcoming variations in appearance for face recognition. Pattern Anal Applic 14, 67–75 (2011). https://doi.org/10.1007/s10044-010-0188-4

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