Abstract
This paper introduces a new subspace classification approach for face recognition. One or more MKL subspaces are created for each individual, starting from the feature vectors extracted through a bank of Gabor filters. The advantages of this method with respect to other well-know approaches are experimentally proved; in particular, our subspace approach effectively captures the intra-class variability, thus allowing to better discriminate between known and unknown faces.
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Cappelli, R., Maio, D., Maltoni, D. (2002). Subspace Classification for Face Recognition. In: Tistarelli, M., Bigun, J., Jain, A.K. (eds) Biometric Authentication. BioAW 2002. Lecture Notes in Computer Science, vol 2359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47917-1_14
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DOI: https://doi.org/10.1007/3-540-47917-1_14
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