Analysis of Facial Features in Identical Twins

A study of the distinctiveness of different facial features (MLBP, SIFT, and facial marks) with respect to distinguishing identical twins is presented. The accuracy of distinguishing between identical twin pairs is measured using the entire face, as well as each facial component (eyes, eyebrows, nose, and mouth). The impact of discriminant learning methods on twin face recognition is investigated. Experimental results indicate that features that perform well in distinguishing identical twins are not always consistent with the features that best distinguish two non-twin faces.

Provided by: Michigan State University Topic: Security Date Added: Dec 2011 Format: PDF

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