Towards a Generalized Eigenspace-Based Face Recognition Framework
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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