Face Recognition by Classification in Eigenspace
نویسندگان
چکیده
Face recognition systems are highly required for variety of applications like user authentication, advanced video surveillance, biometrics etc. Majority of existing systems worked on higher dimensional spaces whereas a human face image (somewhat similar shapes and placement of objects) can be projected on a lower dimensional subspace. This dimensionality reduction is possible by using “Principle Component Analysis” method. PCA approach gives eigenvectors
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تاریخ انتشار 2012