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Face recognizing model using Principal Component Analysis (PCA).

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Face-Recognition-Model

Face recognizing model using Principal Component Analysis (PCA).

This program recognizes a face from a database of human faces using PCA. The principal components are projected onto the eigenspace to find the eigenfaces and an unknown face is recognized from the minimum euclidean distance of projection onto all the face classes.

This application is an effort to implement paper submitted by professors M.A. Turk and A.P. Pentland.

Reference: M. A. Turk and A. P. Pentland, "Face recognition using eigenfaces," Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Maui, HI, 1991, pp. 586-591. doi: 10.1109/CVPR.1991.139758

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Face recognizing model using Principal Component Analysis (PCA).

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