The Performance of Two Deformable Shape Models in the Context of the Face Recognition

In this paper we compare the performance of face recognition systems based on two deformable shape models and on three classification approaches. Face contours have been extracted by using two methods: the Active Shapes and the Bayesian Tangent Shapes. The Normal Bayes Classifiers and the Minimum Distance Classifiers (based on the Euclidean and Mahalanobis metrics) have been designed and then compared w.r.t. the face recognition efficiency. The influence of the parameters of the shape extraction algorithms on the efficiency of classifiers has been investigated. The proposed classifiers have been tested both in the controlled conditions and as a part of the automatic face recognition system.