Projection Incorporated Subspace Method for Face Recognition
نویسنده
چکیده
Two decades of research shows that Principle Component Analysis is effective and convenient for representation and recognition of human face images. It is a kind of subspace method. Many successful face recognition algorithms follow the subspace method and try to find better subspaces for face recognition. In this paper, we present the projection incorporated subspace method based on PCA. This algorithm try to find the optimal subspace by performing PCA on the projection incorporated version of a face image. Experimental results show that this method, compared with the eigenface technique, not only spans a subspace of lower dimension, but also give higher recogntion rates.
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