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19 March 2009 Implications of the advanced mini-max (AMM) classifier on non-cooperative standoff biometrics
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AMM classification is an advanced version of the typical nearest neighbor classifier that allows one to minimize interclass dispersion while at the same time, maximizing intraclass separation. A technique based on the simple orthogonal feature space of Pentland eigenfaces, the combination of these two embodiments will become essential components to a non-cooperative standoff biometric system for military, medical and homeland security applications. The incorporation of robotic assistance further pushes the frontiers of possible surveillance and authentication that can be realized with such a system. The ability to perform out of the line of sight (OLS)-based surveillance adds an additional dimension, and thus novelty, to the already expanding methods to acquire and process environment-specific data.
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Kenneth A. Byrd, Harold Szu, and Mohamed F. Chouikha "Implications of the advanced mini-max (AMM) classifier on non-cooperative standoff biometrics", Proc. SPIE 7343, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VII, 734315 (19 March 2009);

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