Abstract
Eigenspace-based approaches (differential and standard) have shown to be efficient in order to deal with the problem of face recognition. Although differential approaches have a better performance, their computational complexity represents a serious drawback. To overcome that, a post- differential approach, which uses differences between reduced face vectors, is here proposed. The mentioned approaches are compared using the Yale and FERET databases. Finally, a generalized framework is also proposed.
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del Solar, J.R., Navarrete, P. (2002). Towards a Generalized Eigenspace-Based Face Recognition Framework. In: Caelli, T., Amin, A., Duin, R.P.W., de Ridder, D., Kamel, M. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2002. Lecture Notes in Computer Science, vol 2396. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-70659-3_69
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DOI: https://doi.org/10.1007/3-540-70659-3_69
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